What you'll be doing
Core Responsibilities
Agentic system building & evaluation
Design and ship agentic workflows end-to-end — not just prompting, but the surrounding tooling: orchestration, retries, guardrails, and evaluation harnesses
Apply the same core skillset across genuinely different problems — drift detection, content pipelines, and personalization — rather than specializing narrowly in one
Build evaluation loops that catch failures before they reach production, not just after
Search indexing, retrieval & API/MCP integration
Support retrieval infrastructure end-to-end — indexing strategy, relevance tuning, and diagnosing degradation in retrieval quality
Integrate and reason about MCP servers and APIs as a first-class part of system design, not a bolt-on
Editorial judgment & enablement ops
Build systems that make human review of AI-generated content efficient, recognizing that a quality gate is still needed
Partner with Product Management, Product Marketing, Support, and field teams as ongoing stakeholders — not just at requirements-gathering, but throughout the build
What You Bring
3–5 years of relevant software engineering experience, with hands-on work building agentic AI systems, RAG pipelines, or similar retrieval-augmented applications
A systems-first mindset for designing modular AI agents that can scale across disparate data sources without creating technical debt.
Experience mapping complex, end-to-end agentic workflows to anticipate and mitigate failure modes before they reach production.
Experience with search/retrieval infrastructure — indexing, ranking, or relevance tuning
Familiarity with API integration and/or MCP (Model Context Protocol) server integration in agent-based systems
Comfort working cross-functionally with non-engineering stakeholders (PM, PMM, Support, Sales) to translate business content needs into technical systems
Strong judgment on when AI output needs human review vs. when it can ship autonomously
A Big plus
Experience in a fast-moving product company environment (vs. purely research or consulting settings)
Prior experience with content/documentation pipelines, developer enablement tooling, or knowledge-management systems
Experience with drift-detection or sync systems between code and documentation
Familiarity with evaluation frameworks/tooling for LLM-based agents specifically (not just traditional ML evaluation)
#LI-AS1
Alation, Inc. is an Equal Employment Opportunity employer. All qualified applicants will receive consideration for employment without regards to that individual’s race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender identity, age, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law.
The Company will strive to provide reasonable accommodations to permit qualified applicants who have a need for an accommodation to participate in the hiring process (e.g., accommodations for a job interview) if so requested.
This company participates in E-Verify. Click on any of the links below to view or print the full poster. E-Verify and Right to Work.
