Forward Deployed Engineer, Athena

present of AI; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

present of AI in London is seeking a software-focused AI role that blends building production TypeScript code with direct customer work. You’ll connect APIs, deploy agents and turn vague processes into running solutions.

You’ll move between customers, debug in production and explain trade-offs to engineers and operations teams, prioritising reliability over deep specialisation. Experience with prompting, tool use and evaluations is valued.

Qualifications

• Hands-on software development experience.
• Production-grade TypeScript code.
• Experience prompting LLMs and tool calling.
• Ability to run evals and monitor deployed agents.

Responsibilities

• Develop production TypeScript code and connect APIs.
• Turn business processes into deployed agents that run reliably.
• Debug in production and diagnose issues across multiple customers.
• Explain trade-offs to engineers and operations teams.

Skills

TypeScript

LLM prompting

Tool calling

Customer calls

Evals & monitoring

Job description

This role blends hands on software building with direct customer work. A strong candidate writes production TypeScript, connects APIs, and turns vague business processes into deployed agents that keep running. Comfort moving between several customers, debugging in production, and explaining trade offs to both engineers and operations teams matters more than deep specialisation.

How it fits the AI era

The work sits at the point where AI agents meet real customer operations, so much of the job is configuring, evaluating and monitoring agents rather than writing every step by hand. Judgement stays human: scoping what is possible, committing to timelines, and tracing a failure to its root cause. The role rewards people who treat model behaviour as something to test and watch, not trust blindly.

How it builds AI experience

Building here means hands on work with prompting, tool calling, retrieval and evaluations inside an HR data platform, plus agent orchestration and workflow automation. That gives practical grounding in making AI reliable against structured workforce data across onboarding, requests and reporting. Someone preparing for this could build small agent workflows over connected systems and practise writing evals and monitoring for them.

Worth showing

• TypeScript production code
• LLM prompting and tool calling
• Customer facing technical calls
• Evals and production monitoring

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

A modular HR system of record for growing companies, with an add-on AI agent layer aimed at automating onboarding, requests and reporting.