> Markdown version of [/jobs/ext/4126038-applied-ai-software-engineer-lead-ii-ml-engineering](https://www.wearedevelopers.com/jobs/ext/4126038-applied-ai-software-engineer-lead-ii-ml-engineering). 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). --- # Applied AI Software Engineer (Lead II - ML Engineering) - **Company:** UST - **Location:** London, UK - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Software Applications, Automation of Tests, Software Quality, Code Review, Continuous Integration, Python (Programming Language), Machine Learning, OpenAI, Secure Coding, Software Engineering, Systems Integration, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, AgentCore, Agentic-AI, AI Platforms, Api Design, Agent2Agent Protocol - **Published:** October 12, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=03c41f7918f59e53 ## About the Role * Strong software engineering background with Python development expertise * Experience building APIs, integrations, and production applications * Knowledge of LLMs (OpenAI, Anthropic), Agentic AI, and AI-powered workflows * Understanding of CI/CD, automated testing, secure coding, and code reviews * Experience working in Agile teams and collaborating with business stakeholders * Exposure to RAG, vector databases, AWS Bedrock, or enterprise AI platforms is desirable Nice to Have: * AWS Bedrock / AgentCore experience * Vector databases, embeddings & enterprise AI architectures * AI-assisted coding tools * Knowledge of MCP, A2A, and AI orchestration frameworks ## Description * Build and deliver AI-powered applications and workflows. * Develop integrations with APIs, enterprise systems, and LLMs. * Contribute to Agentic AI solutions and automation initiatives. * Collaborate with business and engineering teams to deliver scalable solutions. * Follow best practices in testing, security, CI/CD, and code quality. * Support responsible AI adoption through evaluation and governance.