LLM Engineer

seRevel's AI worker reads POC notes, Slack threads, Jira tickets, and Confluence pages, and turns them into insights and coaching for Sales Engineers. Its users are experts who will check its work, and its output lands in front of customers and sales leadership, so it has to be right, grounded, and fast. You will own that worker end to end: what it retrieves, how it reasons, how you prove it is right, and what it costs to run.

What you will do

• Design and ship the prompts, tools, and agent loops behind seRevel's AI insights, use case intelligence, and AI coaching.
• Build retrieval over POC notes, Slack, Jira, and Confluence so the worker answers from real customer data, not guesses.
• Create evaluation harnesses that catch regressions before SEs do, and use them to decide what ships.
• Put guardrails in place so the worker stays grounded, keeps one customer's data out of another's answers, and fails safely.
• Own cost and latency: measure both, set budgets, and keep the worker fast enough to feel like part of the product.
• Shape how new connectors feed the worker, so each data source lands with the right structure and permissions.
• Talk to the SEs on the team and in the field, and turn what they say into the next iteration.

What we are looking for

• You have shipped LLM-backed features to production and kept them working after launch.
• Strong TypeScript and Node. You are comfortable owning a service, not just a notebook.
• Hands-on experience with retrieval: chunking, embeddings, ranking, and knowing when retrieval is the wrong answer.
• You have built or run evals and can explain why a prompt change was an improvement with more than a vibe check.
• You have designed AI features for users who know more than the model does, and you can say how you kept the AI in the assistant's seat.

Nice to have

• Python for evals and analysis.
• Experience integrating third-party APIs such as Slack, Jira, Confluence, or Salesforce.
• Postgres and Docker in a production setting.
• Background in Sales Engineering, or you have sat through enough POCs to know where they go wrong.