PeopleLoop
AI Engineer
United States · Staff+
Sponsorship not specifiedDetected 35 days ago
PythonNode.jsAPI DevelopmentLLMsRAGA/B TestingLeadershipCollaboration
About the role
- 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.
- This is an applied AI role focused on shipping product using models, not training foundation models from scratch.
Responsibilities
- 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.
- 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.
- Build AI-powered product experiences that help users complete complex workflows faster and with less friction.
- Build and improve ingestion pipelines that use AI to extract and structure data from plan documents and related inputs.
- Design AI features that produce grounded, traceable, and auditable outputs.
- Use models and structured data to power tailored recommendations and decision support for employees, admins, and internal operators.
- 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.
- 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.
Requirements
- 7+ years of software engineering experience, with 2+ years at Senior or Staff level owning cross-team initiatives
- 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 product workflows
- Experience improving latency, cost, reliability, and quality of AI systems
- Ability to evaluate model performance with practical product metrics and user feedback
- Bachelor's degree required, preferably in Computer Science, Engineering, or a related technical discipline
- Strong production experience building AI-powered product features using large language models or similar foundation models
- Strong collaboration skills and ability to work across Product, Design, and Engineering
- Comfort building systems that balance automation with human review and control
- equivalent experience will be considered
- Nice to have
- Experience building AI features in benefits, HR tech, PEO, payroll, insurance, or other compliance-heavy domains
Nice to have
- Familiarity with hosted LLM providers and model APIs
- Experience with prompt engineering, retrieval-augmented generation, or agentic workflows
- Experience with evaluation frameworks, observability, and feedback loops for AI products
- Experience with structured extraction from documents or forms
- Familiarity with graph-based or structured domain modeling
- Human-in-the-loop systems, review queues, or approval workflows
- Experience with multi-tenant or privacy-sensitive production systems
- Comfort with product experimentation and rapid iteration on AI features
Compensation
- PeopleLoop provides competitive compensation including base salary, performance-based bonus programs, equity, and comprehensive benefits package.
- https://www.peopleloop.com/legal/candidate-privacy-policy
Benefits
- 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.
Company info
- 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:
- Our backend is primarily Python, with supporting services in Node/TypeScript.
- 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.
Visa & Work Authorization
- PeopleLoop provides equal opportunity to all applicants without regard to race, color, creed, religion, citizenship, national origin, age, sex, sexual orientation, gender identity, pregnancy, marital status, military or
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This listing is sourced directly from PeopleLoop's careers page and normalized into a canonical job model.