π Senior AI Engineer | Contract | Β£600/day (Inside IR35)
π Canary Wharf (4 days/week on-site)
π 6-Month Contract | Start: ASAP
We are recruiting on behalf of an exciting end client who is building high-impact AI-powered applications that deliver real business value at speed β and they need engineers who think holistically, automate relentlessly, and are fluent in the fast-moving world of AI tooling and infrastructure.
This isn’t a research role. It’s for seasoned engineers who are excited about applying AI in practical, scalable, and production-grade ways.
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π§ What You’ll Be Doing
β’ Designing, developing, and maintaining production-grade AI applications using modern engineering practices (CI/CD, testing, observability, cloud-native)
β’ Building foundational platforms β conversational bots, AI-powered search, unstructured data processing, GenBI β that scale across the enterprise
β’ Working in cross-functional, embedded teams alongside business stakeholders to ship AI solutions fast
β’ Evaluating and integrating LLMs, vector DBs, RAG patterns, and AI agents into robust applications
β’ Championing automation across data ingestion, evaluation, model integration, and deployment
β’ Contributing to internal tooling libraries and AI engineering best practices
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β What Our Client Is Looking For
β’ 5+ years of professional software engineering experience, with a track record of shipping complex systems in production
β’ Strong Python skills (preferred), or Java/similar; solid experience with microservices, APIs, and backend systems
β’ Experience integrating ML models into production (LLMs via APIs, RAG, fine-tuning, embeddings, agents)
β’ Solid grasp of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps
β’ Ability to move fast without sacrificing code quality or operational excellence
β Bonus Points For
β’ Hands-on experience with LangChain, Haystack, Hugging Face, Weaviate, or similar AI/ML tooling
β’ Experience with agentic frameworks: LlamaIndex, CrewAI, AutoGen, or similar LLM orchestration toolkits
β’ Background in platform engineering or internal developer tools
β’ Experience with unstructured data (documents, conversations, images) and transforming it into structured formats
β’ Prior work in a forward-deployed or embedded team model
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