About MetAntz

MetAntz has one of the most advanced GenAI recruitment platforms. We help companies hire faster with an end-to-end product that covers job posting, sourcing, scoring and matching, and AI-driven assessments. We also run a candidate marketplace and a Recruitment as to Service team that fills roles for our customers. In this role you will sell both the platform and the services around it.

The Role

You'll be an engineer who builds AI agents in production, sitting close to the customers who depend on them. This is a full-stack engineering job with an unusually short distance between your code and someone's actual workday. You'll write Go and Python, design schemas, build evals, and present your solution to a senior executive at an enterprise - often in the same week.

What You'll Do

Design and ship production agents. You'll build agents that are mission-critical from day one embedded in Teams, Slack, intranets, voice lines, and email, taking real actions against SAP, ServiceNow, Workday, and a long tail of systems nobody has heard of. These run at enterprise volume under enterprise scrutiny.
Own the full lifecycle. Discovery, build, eval, launch, and the unglamorous months afterward where an agent goes from good to genuinely reliable.
Work directly with the people whose problem it is. You'll sit with leaders at global enterprises, extract the process from their heads, and decide what should be an agent, what should be a workflow, and what should stay human. What You'll Bring

Experience building and scaling end-to-end production systems, with 5+ years of relevant engineering work
Strong backend fundamentals - algorithms, data modeling, and comfort in more than one language, Python and Go especially
Proven problem-solving in fast-changing, ambiguous environments where the requirements arrive in a meeting rather than a ticket
A builder's mindset and high agency - you find a way to ship rather than waiting for the blocker to clear
Comfort working directly with customers
Clear, direct communication with technical and non-technical audiences alike Even Better

You've built or deployed LLM systems in production, and have opinions about evals
Familiarity with agent tooling, RAG pipelines, MCP, and prompt engineering as an engineering discipline rather than a trick
You've been a founder or founding engineer, and know how to balance craft against speed
Experience integrating enterprise applications - HRIS, ITSM, ERP, ticketing - and the authentication that guards them
You've worked with distributed, global teams and multi-tenant SaaS environments

Full-Stack Engineer