Artificial Intelligence Engineer
Posted 1 day ago by eTeam
Negotiable
Undetermined
Remote
London Area, United Kingdom
Summary: As an Agentic AI Engineer, you will design, build, and run AI agents and workflows to enhance engineering productivity. Collaborating closely with engineering teams, you will address their challenges by creating reusable components and modernizing development workflows. Your efforts will facilitate the adoption of AI agents, ultimately improving collaboration and efficiency within the organization. This role requires a blend of technical expertise and strong communication skills to lead workshops and training sessions.
Key Responsibilities:
- Design, build, and run AI agents and workflows to improve engineering processes.
- Collaborate with engineering teams to identify pain points and develop practical solutions.
- Create reusable components, custom agent workflows, and low/no-code agents.
- Facilitate the adoption of modern development workflows and lead training sessions.
- Maintain knowledge bases and ensure effective collaboration with AI agents.
Key Skills:
- Deep experience with agentic platforms and hands-on experience building agents.
- Strong understanding of agent SDKs and frameworks.
- Proficient in modern development workflows and disciplined coding practices.
- Familiarity with agentic protocols and effective interaction patterns.
- Ability to collaborate cross-functionally and run workshops for best practices.
- Hands-on experience with LLM tooling and standardizing agent workflows.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Detailed Description From Employer:
Job Title: Agentic AI Engineer
Location: London, UK (Remote)
Job Type: Full-time contract, 12 Months
Summary:
- As an Agentic AI Engineer, you will design, build, and run AI agents and workflows that meaningfully improve how our engineers work every day.
- You will work closely with engineering teams to understand their pain points and translate them into practical solutions — for example, building reusable components like commands, skills, and CI agents; designing and orchestrating custom agent workflows; developing low/no-code agents for faster adoption; and creating and maintaining knowledge bases connected via connectors and MCP servers.
- You will also help teams adopt modern development workflows (e.g., spec-driven development instead of “vibe coding”) and lead workshops and training sessions to scale these practices across the organization.
- Your work will help our teams shape the new way of working, reduce manual and repetitive work, and unlock new ways of collaborating with AI agents at scale — ultimately improving both developer productivity and the impact we deliver for clients.
Qualifications and Skills:
- Deep experience with agentic platforms
- Hands-on experience building and deploying agents using platforms such as AgentCore, Gemini Enterprise, and Azure Copilot.
- Strong understanding of agent SDKs and frameworks such as ADK, LangChain, and Strands.
- Strong development workflow discipline
- Proficient in modern development workflows (branching, code review, CI/CD, testing, observability).
- Clear understanding of why “vibe coding” (coding without specs, tests, or structure) is harmful at scale.
- Experience using spec-driven development or similar frameworks to design and implement features in a structured way.
- Agentic protocols, communication, and tactics
- Familiarity with key agentic patterns and protocols such as A2A (agent-to-agent communication), MCP (Model Context Protocol), RAG (Retrieval-Augmented Generation), memory management, and context management.
- Ability to design effective interaction patterns between agents, tools, and users.
- Cross-functional collaboration
- Ability to work with engineers, PMs, and other stakeholders to understand their problems and define clear, actionable requirements.
- Experience running workshops, training sessions, and demos to drive adoption and teach best practices.
- Hands-on build experience with LLM tooling
- Have created and maintained Cursor commands, Claude skills, steering documents, and CI agents (or similar equivalents in other tools).
- Comfortable experimenting with and standardizing new agent workflows and tools for wider team use.
Nice to have:
- Experience with enterprise AI governance, safety, and compliance practices.
- Background in developer experience (DevEx), platform engineering, or internal tools.
- Familiarity with observability and monitoring for agents (traces, logs, evaluation frameworks, feedback loops).
- Experience integrating agents with existing systems via APIs, webhooks, and event-driven architectures.