AI Forward Deployed Engineer
AI Forward Deployed Engineer
Posted yesterday
SENIORITY
Lead
About the role
- Partner directly with customers to understand complex business challenges and translate them into scalable AI solutions.
- Design solution architectures and end-to-end AI systems from concept to production.
- Prototype quickly, validate ideas with users, and iterate based on real-world feedback.
- Build production-ready AI applications using modern frameworks, cloud platforms, and best engineering practices.
- Develop intelligent agents, RAG applications, recommendation systems, computer vision pipelines, and machine learning solutions.
- Architect scalable, reliable, and maintainable software systems that integrate seamlessly with customer environments.
- Collaborate with researchers, engineers, product teams, and customer stakeholders to deliver measurable business impact.
- Drive technical decisions around system design, AI architecture, scalability, and performance.
- Help shape both the technical solution and the product strategy from discovery through deployment.
- Continuously evaluate emerging AI models, frameworks, and developer tools to improve how we design, build, and ship software.
- If you have
- Proven experience building production-grade software: 7+ years in software engineering with at least 2 years delivering AI solutions, or 4+ years building AI systems end-to-end.
- Strong Python skills, with hands-on experience in AI-assisted development (vibe coding).Experience with LLMs, Machine Learning or modern AI frameworks.
- Experience with cloud platforms (AWS, Azure, OCI or GCP).Comfortable working with customers and ambiguous problems.
- Strong communication skills.
- Curiosity and willingness to learn continuously.
- AI-first development mindset, with daily use of Claude or similar AI coding tools.
- Advanced English.
- You'll stand out if you have experience with:
- Agentic AI and multi-agent systems.
- LangChain, LangGraph or similar orchestration frameworks.
- Retrieval-Augmented Generation (RAG).Vector Databases (pgvector, Pinecone, Weaviate, Milvus, etc.).Model Context Protocol (MCP).FastAPI or modern Python backend frameworks.
- CI/CD and MLOps practices.
- Building production AI systems at scale.
- Building enterprise software and/or fast-growing startups.
- The industry calls it a Forward Deployed Engineer. At Marvik, we've been building engineers like this for years.
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
