Senior Forward Deployed AI Engineers

Location: London

Company

hirify.global 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

• Build and ship production-quality agentic AI systems, including agent orchestration, tool-use patterns, RAG and retrieval architectures, and reliability layers.
• Design and implement evaluation frameworks and observability for non-deterministic systems.
• Improve build quality through testing, output validation, and automation of manual checks.
• Work directly with client teams, explain technical trade-offs to non-engineers, and communicate business value.
• Improve team practices and contribute reusable assets, reference implementations, and knowledge from client engagements.
• Stay current with AI engineering developments and bring new knowledge back to the team.

Requirements

• Experience building and deploying agentic AI systems into production, beyond proofs of concept or personal projects.
• Experience with multi-step LLM workflows, including tool use and multi-agent orchestration, using frameworks such as Claude Agent SDK, LangGraph, Strands, CrewAI, or a suitable custom implementation.
• Experience implementing RAG or retrieval architectures, including embedding strategies, chunking, hybrid search, reranking, and vector or graph stores.
• Ability to write production-grade code and review code to a high standard; Python is the common language, while strong fundamentals in another modern language are also relevant.
• Experience evaluating LLM systems and forming views on evaluation in enterprise settings.
• Comfort with at least one major cloud provider: AWS, Azure, or GCP, including production deployments with enterprise constraints.
• Experience working with clients or stakeholders outside the immediate team and communicating technically with non-engineers.
• Ability to take ownership in ambiguous situations, make decisions, communicate them, and deliver.

Nice to have

• MCP server development and tool ecosystem integration.
• Experience in Financial Services, Energy, Healthcare, or another regulated environment.
• Experience with model observability tools such as LangSmith or Weights & Biases, and with cost and latency optimisation at scale.
• Writing, speaking, or community contributions 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, partner technical teams, and early capability previews.
• Claude licenses for Chat, Cowork, and Claude Code.
• Flexible learning and development budget and career development pathways.
• Embedded client work focused on building and operating live AI systems in complex industries.
• Exposure to varied enterprise AI engagements and collaboration with leading AI labs.