Agentic AI
Engineer.

The problem you are solving

Executive search is one of the last professional services industries still running on spreadsheets, email threads, and institutional relationships. The information advantage that justified six-month timelines and 25% fees no longer exists. AI can map a talent pool in hours, score candidates against a brief, draft personalised outreach, and surface patterns across thousands of searches. Force was built to run that way from day one.

The AI operating system is what makes Force different from a firm that has bolted a chatbot onto a traditional process. You will be the primary architect and builder of that system.

What you will build

• Multi-agent pipelines for talent market mapping — sourcing, enrichment, deduplication, scoring
• Candidate assessment infrastructure that combines structured data with operator judgment signals
• Outreach automation that operates at scale without losing the quality of a personalised approach
• Intelligence layers that surface market signals — restructurings, promotions, funding events, role changes
• Tooling for the Force search team to run faster, see more, and decide better
• The Benchpark platform back-end — continuous market mapping and succession intelligence

What we are looking for

• Strong Python engineering. You write clean, maintainable, production-grade code.
• Experience building multi-agent AI systems — orchestration, tool use, memory, evaluation
• Comfort working with LLM APIs (OpenAI, Anthropic, or similar) and understanding their failure modes
• Experience with data enrichment, web scraping, or talent intelligence tooling is a strong plus
• You care about the quality of the output, not just whether the pipeline runs
• You work well in a small team where the scope is wide and the feedback loop is short

The stack

Python, Anthropic and OpenAI APIs, LangGraph or similar orchestration frameworks, PostgreSQL, Vercel. We use the best tool for the job — if something works better, we switch. No legacy constraints.

Why this role

Most AI engineering roles are inside large companies where the system you build is one component of a larger machine. At Force, the AI operating system is the product. You will see the full picture — from the brief a client submits to the shortlist they receive — and you will understand exactly what the system needs to do better. The feedback loop between what you build and what it produces is immediate.