Ai Architect (SRK20ST RM 4395)

Source-Right

AI EngineerLondon, England, UKhybridfulltimeIT Services and IT ConsultingPythonLLM APIsOpenAI APIAnthropicagent frameworksRAG workflowsvector storesDockerposted 15 Sep
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Position: Ai Architect (SRK20ST RM 4395)

Sponsorship is not provided. Hybrid mode

Requirements

  • Design, develop, and deliver AI-enabled features and agent-driven workflows that solve real business challenges.
  • Build resilient production systems leveraging cloud-native AI services, agent frameworks, and LLM APIs (e.g., OpenAI, Anthropic).
  • Implement agent-based architectures encompassing reasoning loops, guardrails, observability, and operational controls.
  • Collaborate closely across teams to gather requirements and iterate quickly, employing agile and DevOps principles.
  • Champion quality and security with a “shift-left” testing mindset, ensuring compliance and reliability in AI solutions.
  • Monitor AI system behaviour post-deployment, clearly communicating limitations, risks, and performance.
  • Use AI-assisted coding tools to boost developer productivity and code quality within the team.
  • Engage in continuous improvement through code reviews, evaluation design, and metrics-driven iteration.

Skills You Need

  • Strong software engineering background, with Python‑first development experience.
  • Proven experience building production systems that integrate with LLM API services e.g. OpenAI API services.
  • Hands‑on experience with agentic or tool‑using AI systems, including orchestration, memory, and toolchains.
  • Experience designing and using evals to measure model quality, reliability, safety, and regression.
  • Comfort working with cloud managed AI services and modern agent frameworks.
  • Familiarity with RAG workflows, vector stores, embedding design, and latency/cost trade‑offs.
  • Experience thinking about (and engineering for) failure modes, guardrails, operational reliability, and user impact.

Experience And Qualifications

  • You must have experience the transitioning from traditional software engineering to AI-first environments.
  • Exposure to AWS Bedrock, Azure Foundry, or similar cloud AI agent platforms.
  • Knowledge of interoperability standards (A2A, MCP).
  • Experience with containerisation (Docker, Kubernetes) and modern DevOps tooling.
  • Active contributor to engineering communities, continuous learning, and knowledge sharing.
  • Wealth management experience is a must have