> Markdown version of [/jobs/ext/2727059-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/2727059-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Markit - **Location:** London, UK - **Experience:** Expert - **Salary:** £182,000.0 - £234,000.0 - **Contract:** Temporary to permanent - **Skills:** Artificial Intelligence, Amazon Web Services, Automated Storage and Retrieval Systems, Cloud Computing, Encodings, Communications Protocols, Python (Programming Language), Language Modeling, Open Source Technology, OpenShift, Open Web Application Security, Software Engineering, Systems Integration, Data Ingestion, Large Language Models, Multi-Agent Systems, Software Security, Model Validation, Generative AI, Indexer, Git, SC Clearance, Build Management, Kubernetes, Low Latency, Deployment Automation, Production Code, Machine Learning Operations, Data Pipelines, Docker - **Published:** September 5, 2026 - **Apply:** https://www.totaljobs.com/job/senior-ai-engineer/markit-placements-job107941430 ## About the Role You'll ideally have: * 6+ years of professional software engineering experience, with several years working on LLM-based, generative AI or agentic systems. * A strong track record operating at Senior, Lead or equivalent engineering level. * Commercial experience building multi-agent or agentic AI systems for production, rather than simply integrating existing tools. * Strong Python development skills and excellent software engineering fundamentals. * Hands-on experience with frameworks such as LangGraph, LangChain, Haystack or similar, together with the ability to work below the framework level when required. * Experience designing and deploying AI/ML systems into genuine production environments. * Strong understanding of model inference, latency, performance, data pipelines, state, memory and tool/function calling. * Experience building search and retrieval systems over very large multimodal datasets. * Experience with Docker, Git and cloud platforms, ideally AWS. * Understanding of secure deployment architectures, including air-gapped, on-premises or sovereign cloud environments. * The ability to take technical ownership, make sound systems-level decisions and deliver dependable production software. * Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders. Desirable Experience The following would be advantageous: * Multimodal AI and reasoning. * Edge or offline AI deployments. * Kubernetes, particularly EKS or OpenShift. * MLOps, including model evaluation, monitoring and reproducibility. * Observability for agentic AI systems, including model performance, agent behaviour and drift. * Agent orchestration and inter-agent communication protocols such as A2A. * Model Context Protocol (MCP). * Secure-by-design development principles, including ISO 27001, NIST or OWASP. * Experience within defence, national security or other highly regulated environments. * Contributions to open-source AI/ML projects. Security Clearance Due to the nature of the work, applicants must be eligible to obtain UK security clearance. Candidates will generally need to: * Hold a UK passport. * Have 5 years of continuous UK residency. * Be eligible for BPSS and SC clearance. Clearance sponsorship may be considered for the right candidate. However, given the contract nature of the position, candidates who already hold active, transferable SC clearance are strongly preferred. DV clearance would be an advantage., If you are a senior engineer who enjoys building sophisticated AI systems from first principles and wants to see your work deployed in environments where reliability and accuracy genuinely matter, we'd like to hear from you. ## Description The business is looking for a Senior Applied AI Engineer to take genuine technical ownership of the design and delivery of production-grade agentic AI systems. This is a builder's role rather than an integration role. You will design and implement systems from the ground up, make architecture-level decisions, write production-quality code and own features through to deployment. The systems you build will operate in environments where reliability, security and trust are critical. You will therefore be expected to engineer for real-world conditions, including high workloads, degraded connectivity, secure infrastructure and fully offline or air-gapped deployments. What You'll Be Doing * Design and build multi-agent AI systems from the ground up, using frameworks such as LangGraph, LangChain, Haystack or similar where appropriate. * Develop the orchestration, state management and tool-calling infrastructure required to make agentic systems reliable in production. * Integrate large language models and vision-language models into reasoning, retrieval, summarisation and task-execution pipelines. * Build retrieval, memory, evaluation and guardrail capabilities around AI systems. * Design and implement production pipelines covering data ingestion, processing and inference. * Work with large-scale multimodal datasets spanning text, imagery, telemetry and sensor data. * Design indexing, embedding and retrieval systems capable of operating across multi-terabyte datasets. * Deploy AI systems across cloud, on-premises, sovereign and fully offline environments. * Engineer for reliability, latency, security and predictable failure behaviour. * Build evaluation and observability capabilities to understand model performance, agent behaviour and failure modes. * Take end-to-end ownership of technical workstreams, from architecture through deployment. * Establish engineering patterns and technical direction for other engineers. * Produce clear technical documentation and knowledge transfer to ensure systems can be maintained beyond the engagement. ## Related Videos - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Optimizing Discovery: PostgreSQL's Role in Transforming GetYourGuide's Search](https://www.wearedevelopers.com/videos/1647-optimizing-discovery-postgresql-s-role-in-transforming-getyourguide-s-search) - [The State of GenAI & Machine Learning in 2025](https://www.wearedevelopers.com/videos/1383-the-state-of-genai-machine-learning-in-2025) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)