Define the Future of AI Work

As a Research Engineer at Capably, you’ll help define how intelligent systems operate in real enterprise environments. You’ll work at the intersection of research and production, developing the models, systems, and evaluation approaches that make agentic workflows reliable, repeatable, and deployable at scale.

This role is about turning cutting-edge ideas into practical capability. You’ll explore new approaches in reasoning, planning, tool use, memory, orchestration, and evaluation, then help translate them into systems that improve how Capably’s platform performs on complex enterprise workflows.

Build and Advance Intelligent Systems

We believe strong research is only valuable if it drives real-world outcomes. You’ll design experiments, prototype new methods, and improve system performance across the stack—from prompt and context strategies to evaluation harnesses, model behaviour, and workflow reliability.

You’ll work closely with engineering, product, and deployment teams to understand where current systems break, what high-value workflows require, and how research can expand the complexity of tasks Capably can handle in production. Your work will directly influence the capabilities of the platform and help push beyond what today’s enterprise AI tools can reliably deliver.

• Research and prototype new approaches for agent performance, reliability, and adaptability

• Design evaluations and benchmarks that reflect real enterprise workflows

• Improve model behaviour across reasoning, tool use, memory, planning, and execution

• Collaborate with product and engineering to productionize promising research directions

• Investigate failure modes and develop methods to increase robustness, observability, and repeatability

• Contribute to the systems that expand what Capably’s platform can do without manual intervention

Your work will help Capably strengthen its position as the enterprise AI platform for deploying highly customised AI workflows in production, with built-in security, governance, and auditability.

Success in this role means balancing scientific curiosity with execution. You’ll continuously test ideas, measure outcomes, and refine systems based on what actually improves performance in production. You’ll stay close to the frontier of agent research while keeping a sharp focus on enterprise usefulness, reliability, and scale.

By staying ahead of advances in models, agent architectures, and evaluation methods, you’ll help ensure Capably continues to push the boundaries of what enterprise AI can automate. Your ability to connect research insight with product impact will be essential to shaping the next generation of Capably’s platform.

What You Bring:

1. Strong experience in machine learning, applied AI, or LLM systems engineering

2. A track record of building, testing, and iterating on research-driven prototypes

3. Deep familiarity with model evaluation, experimentation, and failure analysis

4. Strong programming skills and comfort working across research and production code

5. Ability to work across disciplines and translate ambiguous problems into measurable research directions

6. Experience with agents, reasoning systems, workflow automation, or enterprise AI is a strong plus

Your work will help Capably create AI systems that are not just impressive in demos, but dependable in production. If you’re excited to turn frontier research into real enterprise capability, we’d love to hear from you.