Principal Forward Deployed AI Engineers

Location: London

Company

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

What you will do

• Own the technical direction and architecture of complex AI engagements or multiple concurrent engagements.
• Design and build production agentic AI systems, including multi-agent orchestration, autonomous workflows, tool use, state and memory design, failure recovery, and reliability layers.
• Build advanced RAG pipelines covering retrieval architectures, embeddings, reranking, hybrid search, and evaluation frameworks.
• Develop MCP servers, enterprise tool integrations, and evaluation and observability frameworks for non-deterministic AI systems.
• Lead delivery through Lead and Senior FDEs, ensuring quality, timelines, scope, burn, margin, and effective course correction.
• Advise senior client technology leaders, support pre-sales and proposals, develop engineers, create reusable IP and reference architectures, and represent hirify.global in joint engagements with Anthropic.

Requirements

• Experience taking AI systems from ambiguous problems to production deployment, including agentic systems, retrieval architectures, and evaluation frameworks in real organisations with real constraints.
• Experience owning technical direction, making architecture decisions, and being accountable for their outcomes.
• Hands-on production coding experience and readiness to pair with engineers.
• Experience leading delivery teams through planning, sequencing, unblocking, and transparent status communication.
• Experience being the technical face of a workstream, including when delivery was going badly.
• Experience deliberately developing other engineers through mentoring, coaching, or review.
• Experience navigating large organisations, including security reviews, compliance, legacy systems, and multiple teams with different incentives.

Nice to have

• Consultancy background and understanding of consultancy and client commercial models.
• Depth in Financial Services, Energy, or Healthcare.
• Experience shaping or estimating work commercially.
• MCP server development and enterprise tool ecosystem integration.
• Prompt and context engineering, guardrails, and LLM safety patterns in production.
• Experience as a technical founder building under commercial pressure.
• Writing, speaking, or community presence in AI engineering.
• Experience working with Anthropic, Databricks, AWS, or other partner ecosystems.

Culture & Benefits

• Access to Anthropic training, leading AI tools and models, partner technical teams, and early capability previews.
• Flexible learning budget and Claude licenses for Chat, Cowork, and Claude Code.
• Hands-on engineering work on live enterprise systems where reliability and consequences matter.
• Exposure to varied and complex AI engagements across multiple industries.