Chief Forward Deployed Engineer

Quick Facts

• Role: Chief Forward Deployed Engineer

Description

Build end-to-end AI-native systems where LLMs and the agent harness are the core of the value. You will lead agentic system development (agents, workflows, RAG, harness/tool calling, sandboxing, context engineering, caching/compaction), write production-grade Python, and stand up evaluation and observability. You will partner with SMEs and end-users to shape use cases, capture repeatable workflows, and design feedback loops with safe failure handling.

Responsibilities

• Design, build, and ship AI-native systems end-to-end (agents, workflows, RAG, and the harness)

• Implement tool calling, sandboxing, context engineering, sub-agents, caching, and compaction

• Build evaluation pipelines and prove the system is genuinely useful

• Design for failure in the agent loop (retries, model fallbacks, cost limits, human-in-the-loop on consequential actions)

• Capture domain expertise and repeatable workflows for reuse across engagements

• Engage early with clients to shape the use case and validate technical feasibility

• Write production-grade Python (integrations, APIs, data access, deployment)

• Work 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 for task-harness fit and matching context, failures, and policies to the actual task

• Ability to operate close to the client: lead discovery/feasibility and explain trade-offs to technical and non-technical audiences

• Hands-on experience with agentic frameworks (LangChain, LangGraph, Semantic Kernel, or similar)

• Hands-on 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, 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 at least one major cloud (AWS, Azure, or GCP) with containerization and CI/CD

• Sound judgment under ambiguity (scoping, sequencing, speed vs. quality vs. scope)

• English at C1 level

Benefits

• Hybrid work mode by design; remote opportunities within Poland

• Option to work abroad up to 60 days annually

• Business-driven relocation opportunities

• Career development programs

• Thought leadership, mentoring, and soft skills/well-being programs

• Certifications (Anthropic, Gemini, GCP, Azure, AWS)

• 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 perks (entertainment/relaxation zones, table tennis and football, free snacks and coffee)

• Corporate, social, and well-being events

• Note: benefits apply to employees only; contractors may be considered with individually agreed B2B terms