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Mid-level AI role at a well-funded unicorn in a metro with broad responsibilities increases applicant competition.
Highly specialized agentic AI and retrieval expertise limits cross-industry transferability.
Explicit 3–5 year requirement plus mandatory agentic AI, RAG and retrieval expertise makes filters strict.
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Own end-to-end design and engineering of agentic AI workflows including orchestration, retries, guardrails, and evaluation systems for content enablement.
Build and maintain search/retrieval infrastructure with indexing, relevance tuning, and API/MCP server integration for personalized content delivery at scale.
Develop systems enabling efficient human review of AI-generated content collaborating across Product, Support, and Marketing teams throughout the development lifecycle.
3–5 years in software engineering with hands-on experience building agentic AI systems, RAG pipelines, or retrieval-augmented applications.
Experience designing modular AI agents scalable across disparate data sources with failure anticipation and mitigation before production release.
Familiarity with search/retrieval systems including indexing, ranking, tuning, and API or MCP server integration in agent-based architectures.
Comfort working cross-functionally with non-engineering teams (Product Management, Marketing, Support) to translate business needs into technical solutions.
Engineer with a systems-first mindset able to design complex, end-to-end workflows for agentic AI that balance automation with necessary human quality gates.
Experienced in product environments with agile delivery and early ownership of technical systems impacting customer-facing AI experiences.
Skilled at integrating AI content workflows with content management or enablement tooling and capable of implementing drift-detection and LLM evaluation frameworks.