Artificial Intelligence Engineer

Omnis Partners
London, United Kingdom
6 months ago
Applications closed

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πŸš€ Applied AI Engineer – Agentic AI πŸš€

✨ Series A Fintech start-up backed by incredible Founders ✨

πŸ’Ž The kind of equity you actually realise πŸ’Ž



πŸ“ London, Hybrid

πŸ’Έ Β£100k - Β£200k base (level-dependent)

πŸ’² $160k equity vested over four years, with yearly draw-down

πŸ’— Onsite chef, barber, catered breakfasts, gym membership



Join this rapidly scaling AI-native Fintech start-up that’s already raised a significant Series A and is now building its core AI engineering team.



This is a career-defining role, and given the NOISE in the AI job market right now, this is the AI start-up to pay attention to - it could be one of the best career decisions you make. πŸš€



The company is building production-grade agentic AI systems for complex, high-stakes enterprise workflows.



You will work shoulder to shoulder with the Founders themselves, leadership and exceptional peers every day. There are no layers, no hand-offs, and no slow approvals. The intensity is intentional - it’s about learning faster, shipping faster, and taking ownership much earlier than most roles allow.



We're looking for strong software engineers who’ve already put AI systems into production, are comfortable across backend, data, and infrastructure, and don’t flinch when priorities shift. Ambiguity is part of the job. So is growth.



On the work itself: you’ll own large parts of the agentic AI infrastructure end-to-end. That means designing and deploying multi-agent systems, building RAG pipelines, creating evaluation frameworks that actually measure quality and safety, and shipping AI features used by real enterprise customers. You’ll build backend services and APIs (Python, FastAPI/Django), work across infrastructure and deployment pipelines, and ensure everything holds up in production.

You won’t be endlessly tuning prompts or churning out throwaway PoCs. This is about owning systems.



Exceptional engineers choose environments like this because the talent density raises their bar, founder access is direct and unfiltered, and a single year here can compress several years of learning elsewhere.


Now is the time to join at this inflexion point - huge funding round just raised, requirement to scale at a ferocious pace = RAPID career growth for you.



Experience required

  • Educated to at least degree level in a relevant subject; Mathematics, Statistics, Machine Learning, Engineering, Science etc.
  • 4+ years in AI/ML engineering with a foundation in software engineering OR a recent move from pure software engineering into Agentic AI.
  • Hands-on experience building and deploying LLM/agentic systems into production.
  • Strong software engineering foundations: orchestration, memory, deployment, and monitoring is ESSENTIAL.
  • Familiarity with agentic frameworks (LangGraph, ReAct, CoT loops) and/or proven ability to build without them.
  • Knowledge of PyTorch/TensorFlow, RAG, vector databases, and orchestration tools.
  • Background in start-ups (hands-on generalists) or consultancies (client exposure).
  • Independent, entrepreneurial mindset; thrives without hand-holding.



#agenticAI #AIjobs #Softwareengineeringjobs

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Is an AI Forward Deployed Engineer? The Fastest-Growing Job in AI for 2026

If you have been watching AI job boards over the past year, one title keeps surfacing again and again: the forward deployed engineer, or FDE. It has gone from a niche term known mainly to Palantir alumni to arguably the hottest role in the entire AI hiring market. Job postings for forward deployed engineers have exploded, salaries have climbed past levels most software engineers will ever see, and the biggest names in AI β€” OpenAI, Anthropic, Google, Salesforce, Databricks and Palantir β€” are all competing for the same small pool of talent. So what exactly is an AI forward deployed engineer, why has demand surged so dramatically, and how do you position yourself to land one of these roles? This guide breaks it all down for AI engineers, software engineers and data scientists looking at their next move.