Forward Deployed AI Engineer

About the role

A newly formed, dedicated AI team at a large-cap private equity firm is looking for a forward-deployed AI engineer. You will work directly with portfolio companies to assess, design, build and hand off high-impact AI solutions at pace, embedded with full credentials, access and credibility. The goal is to help each company scale an AI opportunity and then hand it off, including helping them hire and build their own capability. This is a remote role requiring fluent English (C1).

Key responsibilities

• Assess AI feasibility during diligence and set technical direction for data products, retrieval pipelines, model orchestration, agentic workflows, evaluation, deployment and monitoring.
• Design and build LLM workflows, retrieval systems and agentic applications against a portfolio company's real enterprise data and infrastructure.
• Define secure, scalable reference architectures across major cloud and AI platform services.
• Establish evaluation and observability standards, including test sets, automated evals, tracing, quality scoring, latency/cost monitoring and regression testing.
• Build human-in-the-loop controls and sound data and security practices by default.
• Develop prototypes that evolve into production systems and transfer knowledge to portfolio company technical teams.
• Evaluate emerging models, frameworks and tools and advise on what is worth adopting.

Required profile

• 5+ years of professional software development, with hands-on production AI/ML systems, including generative or agentic AI.
• Fluent English (C1) to lead technical discussions with executives and portfolio company teams.
• Agile/Scrum experience and comfort working with executives and frontline users.

Required skills

• Deep fluency in agentic tooling (Claude Code, Cursor, Codex, GitHub Copilot) and agentic architecture patterns.
• Modern GenAI patterns: advanced RAG, embeddings, vector/hybrid search, re-ranking, tool/function calling, structured outputs and context engineering.
• Applied ML experience (evals, embeddings, re-ranking, MLOps); classifiers or traditional ML models are a plus.
• Frameworks such as LangChain, LangGraph or LlamaIndex; strong Python.
• Working knowledge of cloud AI/ML platforms (Bedrock, Azure AI Foundry, Vertex AI) and data ecosystems (Snowflake, Databricks, vector databases).
• LLMOps/MLOps standards, versioning, CI/CD, containerisation, cost and performance optimisation.

What we offer

• Stable, long-term contract with opportunities for professional growth.
• Private health insurance and a remote culture promoting work-life balance.
• Ongoing training, mentoring and free access to AI training resources and tools.
• Flexible paid time off and paid holidays.
• Software projects for clients in the U.S. and Latin America, in a diverse work environment.