Location: San Francisco, California or Seattle, Washington
Employment Type: Full time, Hybrid
The Machine Learning team — internally known as \"Potato Radius\" — builds the training pipelines, feature infrastructure, and evaluation systems behind every score Sift returns, across more than 700 customers and a trillion-plus events a year. We are Sift's Data Science and ML Engineering team responsible to ship models fast, prove they work, and trust them in production.
We're hiring a Senior Engineering Manager to lead this team. You're a manager who's inspiring and technical, and who knows how to bring focus to what matters now without losing sight of the long term. You value collaboration and transparency, operate with a get-stuff-done mindset, and bring the technical depth and bias for shipping to spot the manual, brittle, or duplicated work that's quietly slowing the team down. You build a culture of mentorship, give regular and constructive feedback, set clear goals, and grow your team by hiring effectively.
Launch a unified model evaluation framework that gives Data Science fast, trustworthy, apples-to-apples comparisons before a model ever reaches production or shadow traffic.
Evolve core feature infrastructure — including a new global feature store — to improve accuracy and unlock faster experimentation.
Bring a fresh approach to model configuration, replacing tribal knowledge and manual gating with auditable, safely-controlled releases.
Introduce agentic, AI-assisted tooling into customer investigations, automating repetitive data pulls and validation so analysts spend their time on judgment calls, not manual digging.
Build automation that detects an active fraud attack, adjusts score calibration in real time, and cleanly reverts once it subsides.
Lead and grow the team: Own the roadmap, execution, and quality of the systems that train, evaluate, and serve Sift's ML models in production, leading a team of ML platform engineers and data scientists.
Stay technical: Review designs, unblock engineers on hard problems, and make credible calls on architecture and trade-offs.
Drive customer POVs: Partner directly with strategic customers and Sales/Solutions Engineering on technical proof-of-value engagements, translating customer requirements into platform capabilities.
Reduce technical debt: Drive a sustained, measurable reduction in technical debt across the ML platform, balancing new feature delivery with the health of existing systems.
Build evaluation frameworks: Mature the systems that give Data Science and ML Engineering fast, trustworthy signals on model quality before and after deployment.
Automate the ML lifecycle: Identify repeatable, manual processes across training, evaluation, deployment, and monitoring, and drive their automation.
Partner cross-functionally: Align platform investments with business priorities alongside Data Science, Core Infrastructure, Product, and Customer Success.
GCP, AWS, Spark, Kafka, Kubernetes, Docker, Databricks, Python
8+ years of overall hands-on engineering experience, including 4+ years managing software, data science or machine learning engineering teams.
Experience managing Data Scientist and/or in-depth knowledge for data science.
Deep technical fluency in machine learning systems: model training pipelines, feature engineering, model serving, and evaluation at production scale.
Proven track record leading technical customer engagements or POVs, including direct interaction with enterprise customers.
Demonstrated success reducing technical debt in a live, high-traffic production system without stalling feature delivery.
Experience designing or scaling evaluation frameworks (offline and/or online) for machine learning models.
Track record of identifying manual, repeatable engineering processes and driving their automation.
Experience hiring, mentoring, and developing engineering talent.
B.S. or MS/Phd in Computer Science (or related technical discipline), or equivalent practical experience.
Experience with large-scale distributed ML infrastructure such as Spark, Flink, Databricks, or similar.
Familiarity with fraud detection, risk, or trust & safety domains.
Hands-on experience with GCP or AWS ML infrastructure.
Experience with streaming architectures (e.g., Kafka) and containerized/orchestrated deployments (Docker, Kubernetes).
Familiarity with using AI coding assistants (e.g., Claude Code) to accelerate development.
Introduction interview: 30- 45 minutes with a recruiter to discuss your background and the role.
Hiring Manager interview: 30- 45 minutes with the hiring manager to explore your fit for the position.
Hybrid onsite loop with the team: approximately 4–5 hours covering system design, a technical deep dive, a cross-functional stakeholder scenario, and values & behavior.
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Brands including DoorDash, Yelp, and Poshmark rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
Competitive total compensation package
401k plan
Medical, dental and vision coverage
Wellness reimbursement
Education reimbursement
Flexible time off
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems. You won’t just train models in isolation; you will build end-to-end pipelines that extract signals, train custom models per merchant, and serve predictions at production scale with low latency. You will work on an automated machine learning ecosystem that dynamically recalibrates models based on streaming global telemetry data.
Model Development & Refinement: Design, build, and deploy online machine learning models (including ensemble methods, deep learning, transformer architectures and graph-based models) to catch evolving fraud vectors in real time.
Feature Engineering at Scale: Engineer high-frequency time-series features from over 1 trillion behavioral events, optimizing for low-latency signal extraction and pattern recognition.
Production MLOps: Maintain and enhance our automated model training and deployment infrastructure, ensuring frictionless continuous integration and continuous deployment (CI/CD) of newly trained models.
System Optimization: Write high-performance code to minimize scoring latency at runtime, ensuring our core ML services scale seamlessly across distributed databases.
Collaborative Innovation: Work cross-functionally with Core Infrastructure, Product Management, and Data Science teams to translate business-level fraud patterns into robust algorithmic solutions.
Experience: 4+ years of professional experience building and deploying large-scale machine learning models into high-traffic production environments.
Solid Programming Foundations: Strong proficiency in Java or Scala (for our production backend) as well as Python (for data analysis and model prototyping).
Distributed Systems & Big Data: Practical experience with Databricks and big data processing frameworks like Apache Spark, Apache Flink, or Hadoop, and working with NoSQL data stores like Bigtable.
Strong Mathematical Foundations: Deep understanding of statistical modeling, probability, and standard machine learning algorithms (e.g., XGBoost, Random Forests, Neural Networks, and Clustering techniques).
System Design Mentality: Ability to reason through data consistency, pipeline failures, and performance constraints in a distributed, multi-tenant cloud environment (GCP).
Experience explicitly in the fraud detection, risk mitigation, or cyber-security domains.
Deep knowledge of streaming architectures (e.g., Apache Kafka).
Familiarity with containerization and orchestration tools like Docker and Kubernetes.
Familiarity with leveraging AI coding assistants (e.g., Claude Code) to accelerate development and model prototyping
Please note: final stage candidates may be asked to travel for in-person final round interviews.
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
Our Customer Success team partners with leading global businesses to drive adoption of Sift's Digital Trust & Safety solutions. We are subject matter experts on Sift's products and our customers' needs, cultivating trusted relationships that turn product usage into measurable business outcomes. Internally, we are the voice of the customer, and we're always looking for smarter, faster ways to serve our accounts — including experimenting with new AI tools that make our day-to-day work sharper. It's a team that bridges business and technical challenges while helping our customers unlock the full value of Sift's platform.
We're looking for a Customer Success Manager who's eager to build real expertise in a high-stakes, fast-moving industry. You bring sharp critical thinking to a customer's stated request, working to understand the real need behind it, and you build trust quickly with the people you work with — both customers and internal partners. You're comfortable learning a complex product and an evolving fraud landscape, and you reach for the right tools, including AI tools, to work smarter as you grow into the role.
Supporting a portfolio of accounts: Serve as a day-to-day point of contact for a portfolio of accounts, building relationships that go beyond the transactional, with guidance from senior CSMs and your manager on more complex situations.
Diagnosing customer needs: Apply critical thinking to get past a customer's stated request to the underlying need, with an understanding of when to loop in senior team members on ambiguous or high-stakes situations.
Contributing to product adoption: Help customers adopt the Sift platform features most relevant to their goals, and track progress toward measurable outcomes.
Advocating for customers: Represent customer feedback and needs internally, partnering with senior CSMs and other teams on escalations.
Supporting strategic business reviews: Help prepare and contribute to QBRs and other customer-facing reviews, with growing ownership as you build experience.
Building product and industry expertise: Develop a working understanding of Sift's product and the fraud landscape, and start contributing best practices back to the team.
Must-haves:
3+ years of experience in a customer-facing Customer Success, Account Management, or similar role, or equivalent practical experience
Strong critical thinking and problem-solving skills — comfortable working through ambiguous customer situations to find the right solution
Demonstrated ability to build trusted relationships with customers and represent their needs internally
Experience leveraging AI/LLM tools (e.g., ChatGPT, Claude, Cowork) for day-to-day work, and general fluency with AI-assisted workflows
Strong customer-facing communication skills, comfortable with technical and non-technical audiences alike
Nice to have:
Experience in the fraud, payments, or trust & safety industry
Bachelor's degree in a relevant field, or equivalent practical experience
Experience supporting or contributing to strategic business reviews (e.g., QBRs)
Familiarity with SaaS products
Recruiter conversation: 30–45 minutes with a recruiter to discuss your background and the role.
Hiring manager screen: 30–45 minutes with the hiring manager to explore your fit for the position.
Interview loop & presentation with the team: covering a customer scenario walkthrough, stakeholder management, critical-thinking exercises, and values & behavior.
Competitive total compensation package
401k plan
Medical, dental and vision coverage
Flexible lifestyle wallet
Learning & development reimbursement
Flexible time off
Company Mental Health Days
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
As a Director or Sr. Director of Sales at Sift, you are the strategic catalyst driving our revenue growth across top-tier enterprise accounts. You lead and inspire a high-performing sales team, instilling operational rigor while navigating complex enterprise deals and executive relationships. You act as the bridge between field sales execution, executive leadership, and cross-functional partners in Product, Marketing, and Customer Success ensuring our go-to-market strategy aligns with customer needs to scale predictable revenue.
We are looking for a proven enterprise sales leader with a track record of driving complex sales cycles, multi-threading across executive buyers, and instilling operational rigor through MEDDPICC and Command of the Message. You excel at fostering a culture of high execution standards, continuous coaching, and mutual accountability bringing the strategic vision, executive presence, and sales coaching needed to scale top-line revenue and develop world-class sales talent.
Your goal is to drive adoption and partner with our customers as a trusted advisor while building a high-accountability sales team that consistently wins.
Drive Enterprise Revenue & Pipeline Growth: Lead complex sales cycles, enforce multi-threading across executive and technical buyers, and deliver predictable quarterly revenue performance.
Enforce Sales Rigor & Methodology: Operationalize MEDDPICC for deal qualification and Command of the Message for value positioning, conducting deep deal reviews and holding reps accountable to forecast accuracy.
Shape GTM Strategy: Partner with executive leadership to refine enterprise GTM strategy, target account segmentation, and competitive positioning across the digital trust and safety ecosystem.
Coach and Scale Talent: Mentor Enterprise Account Executives through active coaching, joint customer calls, and structured performance management.
Executive Sponsorship & Alignment: Serve as executive sponsor on key enterprise opportunities while aligning customer needs with Product, Marketing, and Customer Success.
Enterprise Sales Leadership: 8–10+ years of Enterprise SaaS sales experience, including 3–5+ years leading and scaling high-performing enterprise sales teams with a track record of consistently exceeding quotas in complex, six-figure+ deal environments.
Methodology Mastery: Operational discipline in applying MEDDPICC deal qualification and Command of the Message value positioning frameworks.
Complex Multi-Threading: Proven ability to execute multi-threaded sales strategies across C-suite executives, Risk/Security leaders, and Finance stakeholders.
Accountability & Coaching Culture: Demonstrated track record of establishing high performance standards, coaching reps, and managing underperformance effectively.
Strategic GTM Vision: Ability to analyze market trends, navigate competitive SaaS landscapes, and collaborate cross-functionally to drive growth.
United States:
Competitive total compensation package
401k plan
Medical, dental, and vision coverage
Flexible lifestyle wallet
Learning & development wallet
Flexible time off
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
About the role
The TAM is Sift's technical product expertise pushed out to the edge, embedded with the customer rather than sitting back in engineering. You're the person who knows the product deeply enough to catch what's about to go wrong in someone's actual environment. We serve as the named, persistent technical partner for Sift's strategic and premium accounts, working in close lockstep with Customer Success so customers get one seamless, aligned strategy rather than a handoff between silos. We connect across Customer Success, Support, Customer Engineering, Trust & Safety Advisory (TASA), Managed Operations, and Product/Engineering to keep every account's technical health ahead of the next escalation.
Operating primarily as a technical diagnostician rather than a builder or purely relationship owner, you excel at reading workflows, analyzing labeling practices, observing score behavior, and catching drift before it becomes an escalation.
You'll build deep, lasting familiarity with each customer's implementation, architecture, workflows, labeling practices, signals, and roadmap, calling out patterns drawn from other customer engagements and your technical expertise. Working in close partnership with Customer Success Managers (CSMs), you translate complex technical findings into meaningful value stories for stakeholders, ensuring you never work in a silo. You are a technical strategy owner and diagnostician, connecting across Customer Success, Support, Customer Engineering, Trust & Safety Advisory (TASA), Managed Operations, and Product/Engineering.
What We're Looking For
We're looking for a Technical Account Manager who operates as a technical diagnostician first: someone who reads workflows, labeling practices, and score behavior closely enough to catch drift before it becomes a fire. You'll build deep, lasting familiarity with each customer's implementation, architecture, and roadmap, and you'll translate what you find into value stories that land with both hands-on engineers and executive stakeholders. This is a partnership role by design — you'll work in close alignment with your paired CSM on every account, never in a silo.
What you'll do
Serve as the named, persistent technical partner for a portfolio of strategic and premium accounts in close alignment with the CSM, acting as a collaborative team player rather than working in a silo.
Build and maintain a technical success plan for each account alongside the CSM, translating technical diagnostics into clear business value stories and executive roadmaps.
Diagnose and guide customers on ongoing best practices for workflow design, labeling strategy, and configuration hygiene, leveraging pattern recognition across your book of business in tandem with the CSM.
Own implementation continuity after go-live in partnership with the CSM, ensuring deep account context survives the handoff from onboarding and technical drift is caught early.
Run recurring technical health reviews and diagnostic readouts with the CSM, surfacing risks early and turning observations into actionable optimization plans.
Help customers navigate model releases with confidence alongside the CSM – analyzing score behavior changes and articulating what they mean for the customer's business goals.
Operationalize TASA's fraud strategy and vertical recommendations inside the customer's Sift environment, working with the CSM to demonstrate tangible business impact.
Coordinate the technical diagnostic and mitigation response during active fraud attacks – orchestrating Support, Customer Engineering, and Product while keeping the CSM and customer informed.
Act as the voice of the customer internally by spotting recurring technical patterns, feature requests, and workflow trends across your book of business and feeding them directly to Product and Engineering.
Act as the primary technical partner to the CSM across Support, Customer Engineering, TASA, Managed Operations, and Product/Engineering so customers receive one seamless, aligned strategy.
Contribute to account retention and growth by catching technical risk early, keeping accounts model-release ready, and cutting down repeat issues, in partnership with the CSM who owns the relationship and renewal conversation.
What you'll bring
5+ years in a technical, customer-facing role – Technical Account Management, Solutions Engineering, Implementation, or Technical Support.
Prior experience in fraud or payments.
Strong pattern recognition skills across APIs, webhooks, JSON, and data logs; able to observe system behaviors, identify subtle anomalies, and diagnose root causes before they become critical failures.
Working SQL and data analysis skills, or the ability to quickly get there, for pulling and interpreting account-specific data.
Familiarity with scripting languages (Python is a plus)
Ability to translate technical detail into business impact for both hands-on engineers and non-technical stakeholders.
A structured, proactive approach to account health – you'd rather catch a stale workflow in a quarterly review than in an escalation.
Comfort operating under pressure during live incidents, with clear, calm communication to the customer throughout.
Ability to augment a work process using AI-tooling.
Strong cross-functional instincts – you know when to pull in Support, Customer Engineering, TASA, or Product, and how to keep everyone aligned.
Familiarity with machine learning concepts well enough to explain model behavior, score changes, and release impact to a customer.
Experience running formal technical health reviews, QBR-style technical readouts, or success planning cadences.
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
Sift is looking for an experienced Senior Sales Engineer to help enterprise and mid-market customers evaluate and adopt our Digital Trust platform. In this role, you will partner closely with Enterprise Account Executives to lead the technical side of complex sales cycles, from discovery and solution design through solution presentations, evaluations, and technical validation.
You will work with some of the world’s largest and fastest-growing digital businesses to understand their fraud, risk, and trust challenges, translate those challenges into solution strategies, and show how Sift can deliver measurable business value. You will engage both technical buyers and executive stakeholders, helping prospects move from technical interest to buying confidence.
This is a high-impact role for someone who enjoys combining technical depth, customer-facing communication, and commercial thinking.
Our Sales Engineering team is made up of creative, technical problem solvers who partner with prospects to understand complex digital trust challenges and design practical, high-value solutions. We work cross-functionally across Sales, Product, Marketing, and Customer teams, and we play an important role in shaping how Sift goes to market.
Senior Sales Engineers at Sift are trusted advisors internally and externally. They bring the voice of the customer into the business, influence product direction through market feedback, and help raise the bar for how we sell, position, and deliver value.
Partner with Enterprise Account Executives to drive complex technical sales cycles with strategic accounts
Lead technical discovery and workshops to understand a prospect’s architecture, workflows, fraud challenges, and business goals
Design and deliver compelling solution presentations and solution narratives tailored to both technical and business audiences
Guide prospects through technical validation, integrations, and proof of value engagements
Translate complex product capabilities into clear customer outcomes and measurable business value
Build credibility with engineers, fraud leaders, operations teams, and executive stakeholders
Surface market feedback and customer requirements to help influence Sift’s product roadmap
Improve internal tooling, knowledge sharing, and repeatable presales processes that make the broader go-to-market team more effective
In this role, you will:
Earn trust quickly with both technical teams and executive buyers
Turn ambiguous customer problems into clear technical solution strategies
Help prospects move faster through evaluation by making Sift easy to understand, validate, and buy
Raise the quality and consistency of technical selling across the team
Bring actionable market insight back into the business to improve product and positioning
5+ years of experience in a Sales Engineer customer-facing technical role
Experience supporting complex enterprise SaaS sales cycles
Strong technical foundation, ideally including APIs, integrations, and data-driven or analytics-oriented platforms
Excellent communication and presentation skills, with the ability to explain complex technical and business concepts to both technical and non-technical audiences
Ability to work effectively across multiple stakeholders and concurrent opportunities
Comfortable using Python or a similar language for demonstrating API usage
Self-starter mindset with strong judgment, curiosity, and a bias toward action
Experience in fraud, payments, risk, trust & safety, or adjacent problem spaces
Experience running POVs, pilots, or technical evaluations for AI/ML-driven products
Familiarity with applied machine learning concepts and an interest in emerging AI trends
Experience building internal automations, tools, or workflows using AI tools or agents
Consultative in how you engage customers whilst still being a natural seller at heart, commercially driven, motivated by winning deals and comfortable owning the outcome with the Account Executive, not just the technical evaluation
Comfortable moving between technical depth and executive value conversations
Curious, collaborative, and resourceful in ambiguous situations
Motivated by helping customers solve meaningful, high-stakes problems
Energized by building, not just supporting, a strong go-to-market motion
Work on high-impact problems at the intersection of fraud prevention, digital trust, and machine learning
Partner with leading enterprise brands across a wide range of industries
Influence not just deals, but also product direction, technical strategy, and how Sift scales its presales motion
Join a team that values technical rigor, customer empathy, and practical execution
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.
Sift is seeking an experienced Enterprise Account Executive to join our team. In this role, you will have the opportunity to help shape the future of fraud prevention for some of the world’s fastest-growing and largest companies.
We are looking for a candidate who brings a strong cross-functional B2B sales approach, with a focus on demonstrating clear value to both business and technical buyers, up to the C-Suite level. The ideal candidate will also thrive in a fast-paced, remote environment and demonstrate a strong ability to adapt to change.
Drive: Must have a hunter mentality to expand Sift’s solutions adoption in our strategic accounts ideal customer profile through value-based selling and clearly articulating our platform differentiation.
Engage: You’ll engage directly with our largest prospects to understand their fraud challenges and how they can be solved with Sift’s machine learning digital trust platform.
Be a consultative problem solver: Sift is disrupting how businesses address the $55B fraud problem. A key component of your job is building tailor-made business cases that demonstrate how Sift is uniquely positioned to solve customers’ fraud problems.
Win as one team: You will demonstrate internal leadership and engage in cross-functional collaboration to drive the platform and process evolution that positions Sift to win.
Shape strategy and scale: You will have an opportunity to shape the strategy and tactics that fuel our continued growth across the globe.
8+ years of high performance in a SaaS sales closing role; preferably in the payments, fraud or security industry
Experience working full cycle sales (prospecting to close)
Ability to build trust with multiple technical decision makers
Strong organisational skills and ability to manage multiple priorities in a high-growth, high-volume environment
Team player: coachable, collaborative, thoughtful, and resourceful with a strong sense of urgency
Knowledge of the FinTech industry is a plus
Knowledge of the payment industry is a plus
Command of the Message and MEDDPICC methodology experience
Let’s build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community – ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: https://sift.com/recruitment-privacy
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.