Member of Technical Staff- Research Engineer (Harness Engineering and Agentic Orchestration)

Overview of the role

We're hiring a Research Engineer to join our AI Research (AIR) team. You'll work on the components that make the outer loop real: how agent harnesses orchestrate model behaviour, how we evaluate what's actually working, how pipelines turn production traces into the next round of improvement, and how we diagnose the failure modes that matter to real users.

These aren't four separate workstreams — they're parts of one system, and we want people who see them that way.

We expect you to sit close to customers — joining calls, watching sessions, reading traces — and to let real workflows shape your research priorities. You'll have meaningful autonomy and the resources to run substantial experiments where the bar for success is shipped impact.

You'll report to our AI Research Lead, and collaborate closely with engineering, product, and design.

You’ll be successful if…

In your first 3 months, you might have shipped a new eval suite for a real customer workflow, improved an agent harness based on trace analysis, or built a pipeline that turns production failures into reusable test cases.

What we're looking for

We're explicitly building coverage across four skill areas. You don't need to be strong in all of them — but you should bring depth in at least one:

• Agent harness and orchestration design — how tools, context, and control flow combine to make a useful agent.

• Agentic eval methodology — task and repo-level evals, dataset curation, the craft of measuring what actually matters.

• Outer-loop and pipeline thinking — feedback loops, training-data flywheels, bandit-style optimisation, anything that goes beyond a single agent session.

• Failure-mode analysis — instrumenting agents, reading traces at volume, surfacing patterns engineering can act on.

Essential

• 4+ years shipping AI/ML products in a startup or applied industry setting, with recent hands-on experience with LLMs and agentic systems.

• Demonstrated depth in at least one of the four skill areas above.

• Strong product and customer instincts: comfort joining customer calls, watching session recordings, and letting real workflows shape what you work on.

• Sharp evaluation judgement: benchmarks where they exist, vibes and quick prototypes where they don't, and the taste to know which is appropriate.

• Experience building datasets for evaluation or training, including the pipeline work that goes with it.

• Deeply curious about agents and excited about reshaping how software is built.

Nice to have

• A Masters or PhD in a relevant computational field.

• Direct experience with coding agents or code-generation systems.

• Background in RL, bandits, or other outer-loop optimisation frameworks applied to LLMs.

• Experience building synthetic data, dataset infrastructure, or internal tooling that other engineers actually used.

• A project you can show us (GitHub links welcome) and a thoughtful answer to "Why Tessl?"

Salary and benefits

Competitive salary commensurate with experience. Health insurance extending to partners and dependents, pension contributions, and the rest of what you'd expect.

Our office is a couple of minutes from King's Cross — pet friendly, with regular team lunches, drinks, and socials. We're hybrid, with Monday, Tuesday, and Thursday as the primary in-office days.