Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations.
Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data.
As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI.
As a Staff Software Engineer on the Platform team, you will work on the core cloud platform that enables all other engineering teams at Qdrant. You’ll design and evolve shared services, control-plane components, and internal APIs that power our managed cloud offering and support enterprise-grade deployments.
This role is about building platform primitives and abstractions, not day-to-day operations. You’ll focus on reducing complexity, improving developer productivity, and driving architectural evolution across the cloud platform.
Design and evolve core platform services and internal APIs consumed by multiple teams.
Drive architectural initiatives such as gRPC migration, eventing/pub-sub foundations, and platform refactors.
Own and improve control-plane and cluster-api components.
Build platform abstractions that reduce operational and cognitive load for other teams.
Write production-grade Go code for platform services and internal tooling.
Collaborate closely with Regions & Clusters, Resilience, and Features teams to enable delivery through platform primitives.
Improve platform scalability, reliability, and developer experience through thoughtful design.
Support production systems and incident response when needed, with a focus on long-term fixes.
5+ years of experience as a software engineer working on platform, infrastructure, or distributed systems.
Strong proficiency in Go and Python, or deep expertise in one with willingness to work regularly with both.
Solid experience with Kubernetes and cloud-native architectures.
Strong understanding of distributed systems and API design.
Experience building and operating production systems used by other engineers or teams.
Comfortable working cross-team and driving technical alignment.
Ownership mindset and clear communication skills.
Nice to have
Experience with gRPC, event-driven architectures, or control-plane systems.
Familiarity with Kubernetes operators or cluster-level abstractions.
Background in SaaS, database, or systems-level product companies.
Experience with observability tooling (Prometheus, Grafana, OpenTelemetry).
Contributions to open-source projects.
A remote-first, international team working on cutting-edge AI infrastructure.
A competitive salary with additional perks.
Flexible working hours and async-friendly culture.
High ownership and real impact.
Open-source, engineering-driven culture.
Choose your own laptop equipment.
For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy.
Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist.
Come build with us!
Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations.
Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data.
As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI.
As a Senior Software Engineer on the Platform team, you will work on the core cloud platform that enables all other engineering teams at Qdrant. You’ll design and evolve shared services, control-plane components, and internal APIs that power our managed cloud offering and support enterprise-grade deployments.
This role is about building platform primitives and abstractions, not day-to-day operations. You’ll focus on reducing complexity, improving developer productivity, and driving architectural evolution across the cloud platform.
Design and evolve core platform services and internal APIs consumed by multiple teams.
Drive architectural initiatives such as gRPC migration, eventing/pub-sub foundations, and platform refactors.
Own and improve control-plane and cluster-api components.
Build platform abstractions that reduce operational and cognitive load for other teams.
Write production-grade Go code for platform services and internal tooling.
Collaborate closely with Regions & Clusters, Resilience, and Features teams to enable delivery through platform primitives.
Improve platform scalability, reliability, and developer experience through thoughtful design.
Support production systems and incident response when needed, with a focus on long-term fixes.
5+ years of experience as a software engineer working on platform, infrastructure, or distributed systems.
Strong proficiency in Go and Python, or deep expertise in one with willingness to work regularly with both.
Solid experience with Kubernetes and cloud-native architectures.
Strong understanding of distributed systems and API design.
Experience building and operating production systems used by other engineers or teams.
Comfortable working cross-team and driving technical alignment.
Ownership mindset and clear communication skills.
Nice to have
Experience with gRPC, event-driven architectures, or control-plane systems.
Familiarity with Kubernetes operators or cluster-level abstractions.
Background in SaaS, database, or systems-level product companies.
Experience with observability tooling (Prometheus, Grafana, OpenTelemetry).
Contributions to open-source projects.
A remote-first, international team working on cutting-edge AI infrastructure.
A competitive salary with additional perks.
Flexible working hours and async-friendly culture.
High ownership and real impact.
Open-source, engineering-driven culture.
Choose your own laptop equipment.
For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy.
Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist.
Come build with us!
Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations.
Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data.
As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI.
We are looking for a Mid-Level Security Engineer to own the hands-on engineering and operational work within our security program. You will be embedded in the Cloud Engineering team, report into the Security Officer, and work closely together to identify risks, set priorities, and drive security issues through remediation. You will act as a security enabler across all Product & Engineering.
Run our public bug bounty program: triage reports, reproduce and validate findings, communicate clearly with security researchers, and drive remediation through to closure.
Investigate reported vulnerabilities at the code level, including our Rust core, Go and Python tooling.
Enable engineers to build secure systems: provide tooling, paved-road defaults, documentation, and practical guidance so security is the easy path, not a checkpoint.
Partner with engineering teams to design, review, and verify fixes, and set clear security requirements on changes where the risk warrants it.
Harden and maintain our GitHub organization’s security posture, including secret scanning, push protection, branch protection and rulesets, dependency alerts, and code scanning, in partnership with the engineering teams that use these repositories daily.
Monitor, investigate, and respond to security alerts across AWS, Kubernetes, CI/CD, and related infrastructure.
Track and report security metrics (vulnerability remediation SLAs, MTTR, patch latency, critical findings) and keep reporting current for the Security Officer.
Implement, configure, and maintain security tooling across our development and cloud environments.
Support security incident response, including investigation, containment, remediation, and follow-up.
Maintain clear, complete, and auditable records of vulnerability and incident work in our tracking systems.
Build security automation and guardrails that scale across the development lifecycle: CI/CD security checks, policy-as-code, GitHub automation, and automated cloud security controls, so secure defaults are enforced by tooling rather than review.
Participate in threat modeling and architecture reviews for new services and major changes.
We are also building out our ISMS, which creates opportunities to contribute to security-tooling evaluations, technical vendor assessments, and proof-of-concept work. Formal compliance ownership, vendor risk assessments, and customer security questionnaires remain with the Security Officer.
This is a hands-on technical role focused on security engineering, vulnerability management, and incident response. The Security Officer owns compliance, formal third-party risk assessments, and customer security questionnaires, allowing you to focus primarily on engineering work. On-call expectations are low: there is no formal rotation, though occasional availability for high-severity incidents is expected.
You can read and navigate an unfamiliar codebase (Rust, Go, Python) well enough to validate a vulnerability report, trace its impact, and judge whether a proposed fix actually closes it.
You write and maintain automation and security tooling comfortably, and can hold a credible technical conversation in code review.
Experience triaging vulnerability reports or working with a bug bounty program, vulnerability disclosure program, product security team, or similar function.
Practical knowledge of cloud and container security, particularly AWS and Kubernetes.
Familiarity with GitHub security features and securing CI/CD pipelines.
The ability to investigate alerts and vulnerabilities methodically, distinguish genuine risk from noise, and recommend proportionate remediation.
Clear written communication skills for working with external researchers and internal engineering teams.
A self-directed approach and comfort independently managing a security queue.
3+ years in a hands-on security engineering, product security, or vulnerability management role.
Nice to have
An offensive security background, such as penetration testing, CTF participation, vulnerability research, or exploit analysis.
Experience working in an open-source company or contributing security improvements to open-source projects.
Familiarity with cloud-native incident response.
A remote-first, international team working on cutting-edge AI infrastructure.
A competitive salary with additional perks.
Flexible working hours and async-friendly culture.
High ownership and real impact.
Open-source, engineering-driven culture.
Choose your own laptop equipment.
For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy.
Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist.
Come build with us!
Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations.
Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data.
As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI.
We're hiring a Business Development Representative to help build Qdrant's enterprise pipeline. You'll report directly to our Enterprise sales leaders and work side by side with them on the accounts that matter most to our growth.
This isn't a role where you'll just work a list. You'll run both inbound and outbound motions, and you'll operate strategically inside key accounts to help identify and drive expansion opportunities alongside the Enterprise team. You'll be a first line of contact for engineering and AI leaders evaluating vector search infrastructure, so a genuine curiosity about how production AI systems are built matters here.
Report directly to Qdrant's Enterprise sales leaders and act as an extension of their account strategy.
Run outbound prospecting into named enterprise accounts, targeting engineering, AI, and data leaders building retrieval and agentic AI systems.
Qualify and progress inbound leads generated by marketing, content, and community channels.
Research target accounts to identify expansion opportunities within existing customers and new logos in strategic segments.
Work closely with Enterprise AEs to develop strategic outreach and multi-threaded account plans for key accounts.
Run discovery conversations to understand a prospect's retrieval, search, and AI infrastructure challenges.
Book qualified meetings and hand off well-scoped opportunities to the Enterprise sales team.
Build outbound workflows using tools like Claude and Common Room to research accounts, personalize outreach, and scale prospecting.
Keep Salesforce and pipeline data accurate and current, and share account and market insights back with sales, marketing, and product teams.
Hit monthly and quarterly targets for qualified pipeline generated.
Up to three years of experience in a business development, sales development, or similar quota-carrying prospecting role, ideally at a technical B2B SaaS or infrastructure company.
A track record of hitting or exceeding pipeline generation targets.
Comfort with both inbound follow-up and proactive outbound prospecting into enterprise accounts.
Strong written and verbal communication skills, with the ability to speak credibly to technical audiences.
A genuine interest in AI infrastructure, vector search, or developer tools. You don't need to be an engineer, but you should be willing to learn the technical fundamentals.
A genuine interest in building a career in sales.
Experience with a CRM (Salesforce) and sales engagement tools.
Organized, self-motivated, and comfortable operating with a degree of ambiguity in a fast-growing company.
You have an understanding of key personas in the AI/ML space.
Familiarity with databases, search, and cloud infrastructure.
Engineering or computer science background.
A remote-first, international team working on cutting-edge AI infrastructure.
A competitive salary with additional perks.
Flexible working hours and async-friendly culture.
High ownership and real impact.
Open-source, engineering-driven culture.
Choose your own laptop equipment.
For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy.
Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist.
Come build with us!
Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations.
Trusted by global leaders like Canva, HubSpot, Tripadvisor, Bosch, and Deutsche Telekom, we’re building the retrieval infrastructure layer for modern AI. Recently raising $50M in Series B funding, we are growing rapidly and committed to transforming how AI understands and interacts with data.
As a remote-first company, we believe diverse backgrounds, perspectives, and experiences fuel innovation. Here, you’ll own meaningful work, tackle challenges, and grow alongside passionate individuals dedicated to shaping the future of AI.
As we expand our presence across Asia-Pacific, we're looking for a Senior Solutions Engineer to be the technical authority in deals that determine how enterprises build AI infrastructure for the next decade, and the trusted technical owner for our most strategic accounts in the region. Most SE roles are demo cycles. This one is different.
You'll work directly with Staff Engineers and CTOs, architect real systems, and own the technical outcome of every engagement you touch, from a first prospect call through to expansion conversations with customers you already support. We care more about time-zone overlap with our regional accounts than a specific city, so this role is open to candidates based anywhere aligned with major APAC hubs like India, Singapore, Japan, or Australia.
Own the technical strategy in enterprise deals from first call to production deployment, partnering with Account Executives to qualify, architect, and close for our entire Asian-Pacific client base
Act as a Technical Account Manager for a small portfolio of existing enterprise customers in the region alongside active prospects, identifying new use cases, expansion opportunities, and upsell paths, and looping in Account Executives and internal resources to advocate for the customer.
Design vector search architectures for high-scale workloads, including multi-tenant agentic systems, hybrid search pipelines, and low-latency retrieval at billion-vector scale.
Build proof-of-concept systems that customers take to production (not throw away), demonstrating Qdrant's performance advantages over JVM-based or proprietary alternatives.
Serve as a trusted advisor on AI infrastructure decisions, helping customers navigate migration from legacy databases, avoid architectural lock-in, and deploy across cloud, on-prem, or air-gapped environments.
Contribute to the field engineering knowledge base: reference architectures, technical guides, and reusable POC frameworks that scale the team's impact.
5+ years of pre-sales or solutions engineering, ideally with a background in data infrastructure or systems architecture. Hands-on infrastructure depth alone isn't enough, we need a proven track record running technical qualification and proof-of-concept processes within a live sales cycle.
Experience designing or operating distributed systems, search infrastructure, or data pipelines at production scale.
Ideally, hands-on experience with RAG (retrieval-augmented generation) pipelines specifically, plus working knowledge of the broader modern AI stack (LLMs, embedding models, agentic frameworks).
Ideally, working knowledge of a structured sales qualification framework such as MEDDICC/MEDDPICC, and the ability to apply it in real deal conversations, connecting technical decisions to business outcomes and deal strategy.
Strong communicator across audiences: you can go deep on indexing trade-offs with a Staff Engineer and explain infrastructure ROI to a CIO in the same afternoon.
Experience with vector search, approximate nearest neighbor algorithms, or semantic retrieval systems.
Background with Rust, C++, or other systems languages.
Familiarity with deployment patterns: Kubernetes, hybrid cloud, on-prem, or air-gapped environments.
A remote-first, international team working on cutting-edge AI infrastructure.
A competitive salary with additional perks.
Flexible working hours and async-friendly culture.
High ownership and real impact.
Open-source, engineering-driven culture.
Choose your own laptop equipment.
For US-based full-time employees, we also offer a comprehensive benefits package including 401k match, health, dental, and vision insurance, plus flexible PTO policy.
Qdrant is an equal-opportunity employer. We believe the best ideas come from diverse teams, and we actively welcome applicants from all backgrounds. If this role excites you but you don't check every single box, we'd still love to hear from you! We don't want to miss out on great people because of a checklist.
Come build with us!