Chief Forward Deployed Engineer

Quick Facts

• Role: Chief Forward Deployed Engineer (AI-native systems)

Description

Build and ship AI-native, LLM-centered agentic systems end-to-end, including RAG workflows, custom tool calling, sandboxing, and context engineering. Own production-grade Python development plus evaluation pipelines and observability to prove real usefulness, while designing robust failure handling (retries, fallbacks, cost limits, and human-in-the-loop). Work with SMEs and end-users to shape use cases, validate that solutions match real workflows, and capture repeatable domain knowledge.

Responsibilities

• Design, build, and ship AI-native systems: agents, workflows, RAG, and the harness/tooling
• Build evaluation pipelines and use them to prove the system is genuinely useful
• Design for failure in the agent loop: retries, model fallbacks, cost limits, and human-in-the-loop on consequential actions
• Capture domain expertise and repeatable workflows so what works on one engagement carries to the next
• Engage early to help shape the use case and confirm technical feasibility
• Write production-grade Python for integrations, APIs, data access, and deployment
• Work directly with SMEs and end-users via interviews, UAT, and workflow observation to validate real-world fit

Requirements

• 7+ years of engineering experience with a strong recent track record building production AI/LLM applications
• Strong agent-design judgment (task-harness fit, matching harness to context, failure/policy alignment)
• Ability to operate close to the client: lead discovery/feasibility and explain technical trade-offs to technical and non-technical audiences
• Hands-on experience with agentic frameworks (LangChain, LangGraph, Semantic Kernel, or similar)
• Experience with major LLM providers (OpenAI, Anthropic, Google Gemini)
• Expert-level Python and solid software engineering fundamentals
• Strong RAG/retrieval skills: vector databases, embeddings, hybrid search, re-ranking, chunking, and context management
• Proven experience evaluating generative AI quality (LLM-based evaluation, heuristics, custom eval frameworks) and using observability/tracing tools (LangSmith, Arize Phoenix, Langfuse, or similar)
• Production deployment experience on AWS, Azure, or GCP with containerization and CI/CD
• Sound judgment under ambiguity (scoping, sequencing, balancing speed vs. quality vs. scope)
• English at C1 level

Benefits

• Hybrid by design; opportunity to work remotely within Poland
• Chance to work abroad for up to 60 days annually; business-driven relocation opportunities
• Career development programs; thought leadership, mentoring, and soft skills/well-being programs
• Certification support (Anthropic, Gemini, GCP, Azure, AWS) and English classes
• Stable pay; Employee Stock Purchase Plan with a 15% discount
• Benefits package (health insurance, multisport, shopping vouchers)
• Referral bonuses up to $2,000
• Office amenities and social/well-being events
• Note: benefits are for employees only; contractors are possible with individually agreed B2B terms