Senior Remote Lead Forward-Deployed AI Engineer

Staffworx Limited; Greater London; Remote; GBP 90,000 - 130,000; Full time

Job summary

Staffworx Limited is seeking seasoned LLM/AI engineers to join a remote-first UK team delivering agentic AI, RAG and prompt engineering projects for enterprise clients.

You will lead design, prototyping and client workshops, shaping technical direction, architectures and guardrails across multi-agent systems, retrieval stacks and semantic layers. Strong consultancy and client-facing experience required.

Qualifications

• 6 to 8 years in software engineering, AI engineering or applied data engineering
• Strong hands-on experience with LLMs, embeddings, RAG, retrieval stacks and vector databases
• Experience designing or implementing multi-agent systems or tool-calling frameworks
• Strong prompt engineering skills, including system prompt design, tool use and structured outputs
• Experience building evaluation frameworks for LLM or agent behaviour
• Strong Python, with experience building production-grade systems
• At least one major cloud AI ecosystem: Azure OpenAI, Google Vertex AI, AWS Bedrock or Anthropic
• Familiarity with semantic modelling, ontologies or knowledge graph concepts
• Proven ability to rapidly prototype solutions for client validation
• Experience working directly with clients in consulting or professional services
• Previous forward deployed, solutions engineering or technical leadership experience
• Commercial awareness and product thinking, including scoping and estimating technical work
• Agent frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel or the OpenAI and Anthropic agent SDKs
• LLM evaluation and observability tools such as Langfuse, LangSmith, Arize or Braintrust
• Deeper ontology or knowledge graph expertise
• Domain experience in life sciences, pharma or healthcare, FMCG or retail, insurance, or banking and financial services

Responsibilities

• Lead technical design within client engagements and set architectural direction across delivery teams
• Work alongside client teams, remotely and on occasional site visits, to understand their workflows, data and constraints first hand
• Turn ambiguous client problems into clear, feasible engineering approaches and fast prototypes for client validation
• Assess client data, platforms, security constraints and operating models
• Contribute to framing, use-case shaping and technical scoping discussions
• Work with client domain experts to surface edge cases and operational realities
• Produce clear, lightweight technical artefacts for client and internal audiences
• Act as the trusted technical voice on the engagement, from first workshop to go-live
• Design and build LLM applications using modern orchestration patterns, prompt frameworks and evaluation loops
• Build multi-agent architectures covering planning, delegation, tool use, memory, safety constraints and monitoring
• Build retrieval and vector-based systems: embeddings, RAG, structured reasoning and semantic workflows
• Connect agents to enterprise platforms through APIs, tools, MCP servers and connectors
• Apply ontologies or knowledge graphs where they improve reasoning and data alignment
• Design, test and version system prompts, tool descriptions and agent instructions
• Build reusable prompt libraries and patterns that hold up across clients and use cases
• Create evaluation sets and automated eval loops to measure accuracy, safety and consistency
• Implement guardrails, structured outputs and explainability checks
• Diagnose and fix failure modes such as hallucination, tool misuse and prompt injection
• Implement evaluation frameworks and safety checks across models and agents
• Design monitoring, logging, tracing and incident-response patterns for live agents
• Apply governance, risk and compliance principles within client environments
• Support releases, environments and handover into client operations
• Ensure reliability, reproducibility, performance and cost control
• Turn field learnings into reusable agent patterns, templates and accelerators
• Feed client insight back into the wider engineering team and its standards
• Coach peers and share new research, tools and techniques

Skills

LLM

RAG

Agentic AI

Prompt engineering

Python

Cloud AI ecosystems

LangGraph

LangSmith

Arize

Knowledge graphs

Tools

LangGraph

CrewAI

AutoGen

Semantic Kernel

LangSmith

Job description

Staffworx Limited is seeking seasoned LLM/AI engineers to join a remote-first UK team delivering agentic AI, RAG and prompt engineering projects for enterprise clients.

You will lead design, prototyping and client workshops, shaping technical direction, architectures and guardrails across multi-agent systems, retrieval stacks and semantic layers. Strong consultancy and client-facing experience required.