Job Opportunities API

Who We Are: PeopleLoop is an AI-powered experience that modernizes benefits and PEO solutions for people-driven companies. It reduces complexity and errors across critical people operations, gives leaders clearer insight into compensation and benefits costs, trends, and tradeoffs, and delivers a more modern employee experience. Visit PeopleLoop.com http://PeopleLoop.com or follow us on LinkedIn https://www.linkedin.com/company/peopleloopinc/ to learn more. We’re rethinking the space end-to-end—pairing structured data, AI-powered workflows, and modern product experiences to help HR admins, brokers, and employees get better outcomes with less manual work. In this role, you’ll build AI features that are embedded directly into the product experience. You’ll work on systems that use large models to ingest documents, support compliance reasoning, power personalized recommendations, and automate complex workflows. This is an applied AI role focused on shipping product using models, not training foundation models from scratch. As a Staff-level engineer, you’ll set patterns, mentor engineers, drive design reviews and RFCs, and help define how AI is built and operated across the product. Our backend is primarily Python, with supporting services in Node/TypeScript. What you get to do: - AI Product Features: Build AI-powered product experiences that help users complete complex workflows faster and with less friction. Apply large models to real customer problems across admin, broker, and employee journeys. - Model Integration and Optimization: Work directly with model endpoints and APIs, integrating hosted LLMs into production systems. Tune latency, reliability, throughput, token usage, and cost while maintaining quality and trust. - AI Plan Ingestion: Build and improve ingestion pipelines that use AI to extract and structure data from plan documents and related inputs. Focus on practical performance, quality, and operational reliability. - Explainable Outputs: Design AI features that produce grounded, traceable, and auditable outputs. Make sure users can understand how recommendations were generated and what source data they are based on. - Personalized Decision Support: Use models and structured data to power tailored recommendations and decision support for employees, admins, and internal operators. - Prompting, Retrieval, and Tool Use: Develop systems that combine prompts, retrieval, and internal tools to produce useful outcomes. Build guardrails, fallbacks, and structured output patterns that make model behavior dependable. - Evaluation and Quality: Create evaluation workflows to measure accuracy, grounding, completeness, and user impact. Use offline tests, human review, and production feedback to continuously improve AI features. - AI + Human-in-the-Loop Workflows: Design workflows where the model assists users, but humans review, approve, and correct when needed. Build systems that learn from feedback and improve over time. - Cross-Functional Collaboration: Partner closely with Product, Design, and domain experts to identify where AI adds the most value, define acceptable failure modes, and turn ambiguous workflows into production-ready features. - Technical Leadership: Set engineering standards for AI feature development, mentor other engineers, and help establish the patterns that will scale AI across the product. What you bring: - 7+ years of software engineering experience, with 2+ years at Senior or Staff level owning cross-team initiatives - Strong production experience building AI-powered product features using large language models or similar foundation models - Experience integrating and optimizing model endpoints in production - Strong Python experience, with working knowledge of modern backend or API development - Experience shipping features that use LLMs, retrieval, tool use, prompts, or structured outputs - Comfort working with large models and applying them to real produc