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Build AI That Acts, Not Just Answers
AI Agent Engineer — Full-time · Remote-first
This role opens following our first funding round. AI agent engineering is one of the fastest-moving disciplines in the industry right now — if you're already building in this space, we'd like to hear from you.
About the Role
Most AI products do the same thing: take an input, call a model, return an output. The hard part — the genuinely interesting part — is building systems where AI doesn't just respond, but reasons, plans, uses tools, and acts across multiple steps to achieve an outcome. That's what AI agents are. And right now, the people who know how to build them well are rare.
myCandr today analyses employee feedback and surfaces insights. But the vision is broader: AI that doesn't just tell organisations what their people are saying, but helps them act on it. Agents that can move across systems, generate recommendations, draft communications, and trigger workflows — all grounded in what employees are actually experiencing.
This is a founding role in that evolution. You won't be maintaining a system someone else designed. You'll be architecting what the next generation of myCandr looks like — both in the product and across the company's internal operations.
What You'll Build
- Multi-step agentic workflows that move beyond analysis into recommendation and action
- The orchestration layer that coordinates AI agents working across tools, data sources, and outputs
- Internal AI agents that automate operational functions — from pipeline research to customer onboarding support
- Tool integrations that give our agents the ability to read, reason, and respond across the systems our customers use
- Evaluation frameworks for agentic systems — because an agent that acts unpredictably is worse than one that doesn't act at all
- The architecture that will define how myCandr evolves from an analysis platform into an action platform
What We're Looking For
- Hands-on experience building agentic AI systems — you've shipped agents that do real work, not just demos
- Deep familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, or similar) and orchestration patterns
- Strong engineering fundamentals — you build systems that are robust, observable, and maintainable
- Understanding of tool use, RAG architectures, and multi-agent coordination
- A practical, grounded approach to AI — you know where agents break and how to design around it
- Product curiosity — you think about what the agent should achieve for the user, not just what it technically can do
- You stay close to how this field is moving and have strong opinions about where it's going
Agentic AI is one of the most consequential engineering disciplines of the next decade.
The people who build serious agent systems now — who understand the failure modes, the trust challenges, the orchestration complexity — will be the architects of how organisations actually use AI. We're offering that opportunity on a problem that genuinely matters.
Register Your Interest
Fill in the form below and tell us about an agentic system you've built — what it did, where it broke, and what you learned.
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