Forward Deployed Engineer
Qdrant is on a mission to revolutionize how companies harness vector search to power cutting-edge AI applications. As the creators of the open-source Qdrant vector database, we help organizations scale similarity search and semantic search for unstructured data like text, images, and audio. Our stack is trusted by developers, enterprises, and startups globally.
We're a remote-first company with a strong engineering culture and a passion for open-source. Now, we're looking for exceptional Forward Deployed Engineers to bridge the gap between our customers and our core technology.
About the Role
As a Forward Deployed Engineer (FDE) at Qdrant, you'll work directly with our customers to implement advanced vector search solutions. You will deeply understand client needs, design technical solutions using Qdrant, and ensure successful deployments. You're not just a coderâyou're a strategic advisor, an architect, and a hands-on engineer.
This role is ideal for someone who thrives at the intersection of engineering, product, and customer success.
Tasks
What Youâll Do
Work closely with customers to design, deploy, and optimize vector search applications using Qdrant.
Translate complex requirements into scalable technical solutions, often involving natural language processing (NLP), machine learning (ML), and unstructured data.
Develop prototypes, integrations, and reference implementations to demonstrate best practices.
Provide technical guidance and hands-on assistance during proof-of-concept and production rollouts.
Act as a feedback loop between customers and Qdrantâs product & engineering teams to influence roadmap decisions.
Create technical documentation, sample projects, and internal tooling to accelerate customer success.
Requirements
3+ years of experience in software engineering, solutions architecture, or a similar technical customer-facing role.
Strong DevOps/MLOps and infrastructure skills. Hands-on K8s experience is a MUST.
Proficient in Python, JS/TS, or similar languages used in backend systems and AI pipelines.
Solid understanding of vector search, embeddings, or machine learning fundamentals.
Experience integrating APIs, databases, and cloud-native infrastructure (e.g., Docker, Kubernetes, CI/CD pipelines).
Excellent communication and problem-solving skills, especially in customer-facing situations.
Comfortable working in a remote, async-first, startup environment.
Prior work in developer relations, pre-sales engineering, or post-sales support.
Benefits
Work on cutting-edge AI infrastructure with a global open-source community.
Be part of a remote-first, high-trust, and collaborative culture.
Influence the trajectory of a fast-growing startup.
Competitive compensation, equity options, and generous vacation policy.
We are looking preferably for US east/central timezones.About the companyQdrant is powering the next generation of AI applications with advanced, high-performant vector similarity search technology. Our flagship product is the leading open-source Vector Database. https://github.com/qdrant/qdrant
Apply Now
We're a remote-first company with a strong engineering culture and a passion for open-source. Now, we're looking for exceptional Forward Deployed Engineers to bridge the gap between our customers and our core technology.
About the Role
As a Forward Deployed Engineer (FDE) at Qdrant, you'll work directly with our customers to implement advanced vector search solutions. You will deeply understand client needs, design technical solutions using Qdrant, and ensure successful deployments. You're not just a coderâyou're a strategic advisor, an architect, and a hands-on engineer.
This role is ideal for someone who thrives at the intersection of engineering, product, and customer success.
Tasks
What Youâll Do
Work closely with customers to design, deploy, and optimize vector search applications using Qdrant.
Translate complex requirements into scalable technical solutions, often involving natural language processing (NLP), machine learning (ML), and unstructured data.
Develop prototypes, integrations, and reference implementations to demonstrate best practices.
Provide technical guidance and hands-on assistance during proof-of-concept and production rollouts.
Act as a feedback loop between customers and Qdrantâs product & engineering teams to influence roadmap decisions.
Create technical documentation, sample projects, and internal tooling to accelerate customer success.
Requirements
3+ years of experience in software engineering, solutions architecture, or a similar technical customer-facing role.
Strong DevOps/MLOps and infrastructure skills. Hands-on K8s experience is a MUST.
Proficient in Python, JS/TS, or similar languages used in backend systems and AI pipelines.
Solid understanding of vector search, embeddings, or machine learning fundamentals.
Experience integrating APIs, databases, and cloud-native infrastructure (e.g., Docker, Kubernetes, CI/CD pipelines).
Excellent communication and problem-solving skills, especially in customer-facing situations.
Comfortable working in a remote, async-first, startup environment.
Prior work in developer relations, pre-sales engineering, or post-sales support.
Benefits
Work on cutting-edge AI infrastructure with a global open-source community.
Be part of a remote-first, high-trust, and collaborative culture.
Influence the trajectory of a fast-growing startup.
Competitive compensation, equity options, and generous vacation policy.
We are looking preferably for US east/central timezones.About the companyQdrant is powering the next generation of AI applications with advanced, high-performant vector similarity search technology. Our flagship product is the leading open-source Vector Database. https://github.com/qdrant/qdrant
Apply Now