Artificial Intelligence Engineer

Omnis Partners; City Of London; Hybrid; GBP 130,000 - 160,000; Full time

Job summary

A global consulting powerhouse is seeking a Lead Engineer in Agentic AI Systems to design and build advanced multi-agent systems. The role offers significant technical autonomy in a start-up-style environment and is ideal for someone who prefers building over advising. Applicants should have strong AI/CS academic backgrounds and hands-on experience in leading teams while maintaining close involvement in coding. The salary ranges from £130k to £160k plus bonuses, with flexible work arrangements involving some client site travel.

Qualifications

• Proven experience of building production agentic AI, ML, or AI engineering systems from scratch.
• A history of technically leading teams while staying hands-on.
• Familiarity with agentic frameworks (ReAct, LangGraph, tool orchestration).

Responsibilities

• Architect multi-agent systems (ReAct, CoT loops, LangGraph) from scratch.
• Scale deployments across SQL workflows and distributed compute.
• Provide hands-on technical leadership to high-performing engineers.

Skills

Hands-on technical leadership

Strong communication skills

Deep software engineering foundations

Familiarity with agentic frameworks

Education

Strong academic background in AI / Computer Science / Machine Learning (MSc / PhD ideal)

Tools

PyTorch

TensorFlow

Vector DBs

Job description

Lead Engineer – Agentic AI Systems

🚀 Start-up-style engineering team inside a global consulting powerhouse

🚀 Peer group of world-class AI engineers and researchers

🚀 Own and build production-grade multi-agent systems end-to-end

🚀 High-velocity environment with huge technical autonomy

💸 £130k – £160k + bonus

📍 UK-wide flexible / some travel required to client site

We’re hiring a deeply technical, hands-on Agentic AI Technical Lead to design, build, and ship advanced multi-agent systems used in real-world enterprise and government environments.

This role is ideal for someone who loves building , not just advising : think Forward Deployed Engineer , Principal / Staff AI Engineer , or Member of Technical Staff who’s ready to lead technically , own architecture, and guide an engineering team—without stepping into corporate exec-land.

You’ll set technical direction, define engineering standards, and stay extremely close to the codebase while working with some of the strongest Agentic AI talent in the industry.

What You’ll Build & Lead

• Architect multi-agent systems (ReAct, CoT loops, LangGraph, MCP) from scratch
• Productionise agentic systems with evaluation, observability, and rigorous testing
• Scale deployments across SQL workflows, pandas, RAG pipelines, and distributed compute
• Define modern evaluation standards (Pass@N, multi-run testing, tool reliability gates)
• Lead client technical sessions and shape solution design (no exec stakeholder wrangling)
• Provide hands-on technical leadership to high-performing engineers
• Stay ahead of frontier LLMs, orchestration frameworks, and agent-design innovations

What You Bring

Required

• Strong academic background in AI / Computer Science / Machine Learning (MSc / PhD ideal)
• Proven experience of building production agentic AI , ML, or AI engineering systems from scratch
• A history of technically leading teams while staying hands-on
• Deep software engineering foundations : deployment, evaluation, monitoring, optimisation
• Familiarity with agentic frameworks (ReAct, LangGraph, tool orchestration)
• Strong communication skills for technical workshops and solution shaping

Preferred

• Experience with PyTorch / TensorFlow, vector DBs, RAG, distributed inference
• Background in start-ups, high-performance engineering groups, or technical consulting
• Experience navigating complex industries or regulated environments
• Bias toward action, experimentation, and independent delivery

Why Join

This is a rare opportunity to lead without leaving the code , shaping one of the most advanced Agentic AI engineering capabilities in the consulting world.

You’ll work in an environment that prioritises experimentation, fast iteration, and technical impact—building real systems, not slideware.