Lead Forward Deployed AI Engineers

Location: London

Company

hirify.global AI deploys production AI systems for complex organisations and partners with Anthropic, AWS, Microsoft, and Databricks across Financial Services, Energy, and Healthcare.

What you will do

• Lead AI engineering engagements end to end, from solution design through production deployment in complex enterprise environments.
• Design and build production agentic AI systems, including multi-agent orchestration, autonomous workflows, tool-use patterns, and reliability layers.
• Build advanced RAG pipelines covering retrieval architectures, embeddings, reranking, hybrid search, and evaluation frameworks.
• Develop MCP servers and enterprise tool integrations, and create evaluation and observability frameworks for non-deterministic AI systems.
• Own senior-level client technical relationships, manage organisational complexity, identify commercial opportunities, and maintain delivery momentum.
• Mentor AI Engineers, codify repeatable deployment patterns, contribute reference architectures and methodologies, and work with Anthropic field teams on joint engagements.

Requirements

• Experience taking AI systems from ambiguous problems to production deployment inside real organisations with real constraints, including agentic systems, retrieval architectures, and evaluation frameworks.
• Experience owning technical direction, making architecture decisions, and being accountable for their outcomes.
• Hands-on production coding experience and willingness to work directly in the codebase and pair with engineers.
• Experience leading delivery teams through planning, sequencing, unblocking, and transparent status management.
• Experience acting as the technical face of client work, including during difficult delivery situations.
• Experience deliberately developing engineers through mentoring, coaching, or review.
• Experience contributing to commercial work shaping or estimation.
• Experience navigating large organisations, including security reviews, compliance, legacy systems, and multiple teams with different incentives.

Nice to have

• Depth in Financial Services, Energy, or Healthcare.
• MCP server development and enterprise tool ecosystem integration.
• Prompt and context engineering, guardrails, and production LLM safety patterns.
• Experience as a technical founder who built something from nothing under commercial pressure.
• Writing, speaking, or community presence in AI engineering.
• Experience working with partner ecosystems such as Anthropic, Databricks, or AWS.

Culture & Benefits

• Access to Anthropic training, leading AI tools and models, Claude licenses, and early capability previews.
• Flexible learning and development budget with career development pathways.
• Hands-on engineering environment with direct involvement in live client systems and complex enterprise problems.
• Opportunities to work jointly with leading AI lab teams and across Financial Services, Energy, and Healthcare.