Key skills
Agentic AI applicationsAI lifecycle componentsAI frameworks for agent workflowsCloud model platformsPythonSQLData engineeringSemantic modelsSemantic layersGoAILangChainAgenticData EngineeringAnalyticsBedrockSDLC
About this role
Harnham is a specialist data and AI recruitment firm, and they are seeking a Forward Deployed Engineer focused on Agentic AI systems. The role involves building production-ready agent workflows and developing semantic models to enhance the AI software delivery lifecycle while collaborating closely with stakeholders.
Responsibilities:
- Build agentic workflows for the AI SDLC that review requirements, identify gaps, and produce a deployment risk score before changes go live
- Design and implement guardrails and evaluation checks so agents behave reliably across different change scenarios
- Develop semantic models and semantic layers that connect business meaning to data and AI outputs
- Partner with data and analytics teams to connect AI workflows to production data pipelines and datasets
- Write and review production Python and SQL, and debug code generated with AI coding assistants
- Work directly with stakeholders to clarify requirements, define success criteria, and communicate tradeoffs clearly
Requirements:
- Experience building Agentic AI applications end to end, including core lifecycle components (retrieval, tools, planning, memory or state, and guardrails)
- Hands-on experience with at least one AI framework used for agent workflows (for example LangChain) and cloud model platforms (for example Bedrock or similar)
- Strong Python and SQL skills, with the ability to debug and reason about code behaviour
- Strong data engineering background, with experience connecting AI work to real data systems and pipelines
- Comfortable working in stakeholder-facing environments and explaining technical decisions in plain language
- Proven ability to deliver quickly in an ambiguous environment and take ownership
- Strong understanding of agent theory, evaluation methods, and failure modes
- Experience building semantic layers, business-facing data models, or metric definitions
- Experience with vector search, embeddings, and retrieval-augmented generation patterns at production scale
- Prior experience as a forward deployed engineer, solutions engineer, or delivery-focused AI engineer