Chief Forward Deployed Engineer

Quick Facts

• Role: Chief Forward Deployed Engineer

• Focus: Build AI-native agentic systems with LLMs at the core

Description

You will design, build, and ship end-to-end AI-native systems (agents, workflows, RAG, and supporting harness) where LLM value delivery is proven with evaluation pipelines and observability. You will write production-grade Python, design agent failure handling (retries, model fallbacks, cost limits, and human-in-the-loop for consequential actions), and create feedback loops that capture repeatable workflows. You will work closely with SMEs and end-users to shape use cases, validate fit with real workflows, and extract domain expertise for reuse.

Responsibilities

• Design, build, and ship AI-native systems end-to-end: agents, workflows, RAG, and the harness (custom tool calling, sandboxing, context engineering and sub-agents, caching, compaction)

• 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 to reuse across engagements

• Engage early to shape the use case and confirm technical feasibility

• Write production-grade Python for integrations, APIs, data access, and deployment

• Collaborate with SMEs and end-users via interviews and UAT; observe real workflows and validate fit

Benefits

• Hybrid work mode with option to work remotely within Poland

• Opportunity to work abroad up to 60 days annually

• Career development programs, mentoring, and soft skills/well-being programs

• Certifications and English classes

• Stable pay and Employee Stock Purchase Plan (15% discount)

• Health insurance, Multisport, shopping vouchers

• Referral bonuses up to $2,000

• Corporate, social, and well-being events

• Option for contractors (B2B terms agreed individually)

Requirements

• 7+ years engineering experience with production AI/LLM application delivery

• Strong recent track record building production AI/LLM applications (not prototypes or research only)

• Strong agent-design judgment (task-to-harness fit, failure handling, policies)

• Ability to operate close to clients: lead discovery/feasibility with SMEs and end-users and explain 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 strong software engineering fundamentals

• Strong RAG/retrieval skills (vector databases, embeddings, hybrid search, re-ranking, chunking, context management)

• Proven LLM evaluation experience and observability/tracing tools (LangSmith, Arize Phoenix, Langfuse, or similar)

• Production deployment experience on AWS/Azure/GCP with containerization and CI/CD

• Sound judgment under ambiguity (speed vs quality vs scope)

• English at C1 level