At M-KOPA, you'll lead the AI Ops Agents team from day one — owning delivery, growing the function, and proving the value. You'll work daily with Claude, Claude Code, MCP, and LangChain to build production-grade agents and automations that internal teams actually use. Your team builds automations and agents for internal use and serves as internal consultants, helping Software Engineering teams integrate AI into customer-facing products.
Key Responsibilities:
- Lead and Mentorship: Lead three AI Ops Engineers — own their delivery, development, and day-to-day work.
- Prioritize efficiently: Manage competing requests from multiple teams by applying a clear prioritisation framework you'll help develop and improve.
- Design and ship: Design and ship multi-agent systems and production-grade automations that measurably improve how internal teams and customer-facing staff work.
- RAG Pipelines: Build RAG pipelines for internal knowledge retrieval that ground agents in real organisational context.
- AI Tooling Stack: Keep the AI tooling stack healthy as usage scales across 2,500+ employees.
- Stay current: Keep up with emerging AI tools and technologies - know what's hype and what's actually useful.
- AI Training: Help refine AI training for the wider organisation, including Software Engineering teams.
Technical Environment:
- AI & Agentic Frameworks: Claude, Claude Code, Anthropic tooling, LangChain, LangGraph, MCP, multi-agent orchestration, Google ADK (or similar agentic tooling)
- Automation & Prototyping: Scripting, workflow tools, AI-assisted development, rapid prototyping (Vercel/Railway)
- Enterprise Tooling: Identity automation (Entra), internal platforms, Notion, HiBob integrations
- Existing Foundation: Twelve months of Claude, Claude Code, Notion, HiBob, and Entra automations already running in production — you're building on proven foundations, not starting from zero
Our Approach:
- Build, don't just advise: This is a hands-on team that ships working automations and agents.
- Prove the value, then expand: Start with three engineers, demonstrate impact, grow from there.
- Product-focused mindset: Treat internal teams as customers and build tooling that works.
- Cut through the hype: Evaluate emerging AI tools on practical value, not marketing buzz.
Requirements:
- Hands-on experience building production-grade automations and AI agents — scripting, workflow tools, or AI-assisted development.
- Hands-on experience building multi-agent systems using agentic frameworks — LangChain, LangGraph, MCP, Google ADK or similar.
- Experience with RAG pipelines — retrieval-augmented generation for internal knowledge and workflow automation.
- Background in enterprise tooling — rapid prototyping tools (Vercel/Railway), identity automation (Entra), or internal platforms.
- People leadership experience — you've led or mentored engineers and can own a team's delivery and development.
- BA/BSc/HND degree qualification.
.png){kind=logo}
