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# Principal Engineer HR AI Solutions

- **Company:** Harman Professional, Inc.
- **Location:** Novi, MI, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Cloud Computing, Computer Programming, Continuous Integration, Custom Software, Data Governance, Software Debugging, Decision Support Systems, Distributed Systems, Human Resources Information System (HRIS), Jinja (Template Engine), Python (Programming Language), Machine Learning, Microsoft Software, Node.Js, NoSQL, NumPy, Ui Patterns, Search Technologies, SQL Databases, TypeScript, Workflow Management Systems, ReactJS, Large Language Models, Grafana, Prompt Engineering, Model Validation, Generative AI, Backend, Fastapi, Pandas, Containerization, Scikit Learn, Kubernetes, Low Latency, Graphql, Terraform, Software Version Control, Workday, Docker, Servicenow
- **Published:** July 29, 2026
- **Apply:** https://jobs.mitalent.org/job-seeker/job-details/JobCode/398064510

## About the Role

Experience: 8+ years of experience building production software or data products, including hands-on experience with ML, LLMs, Generative AI, or AI-enabled workflow automation.
AI and GenAI foundations: Strong conceptual and practical understanding of LLMs, embeddings, RAG, agentic workflows, prompt engineering, model orchestration, model evaluation, guardrails, and responsible AI practices.
Programming: Proficiency with Python, such as FastAPI, NumPy, Pandas, scikit-learn, Pydantic, and Jinja2, plus Node.js or TypeScript; strong experience with APIs, distributed systems, and integration patterns.
Full-stack delivery: Ability to build internal applications, dashboards, copilots, and workflow tools using modern front-end and back-end patterns, such as React, REST or GraphQL services, and reusable UI/data components.
Data and search: Experience with SQL and NoSQL databases, search and analytics platforms, vector databases such as Pinecone, Weaviate, FAISS, Milvus, or pgvector, and practical knowledge of chunking, reranking, retrieval quality, and data-product design.
Model providers and frameworks: Working familiarity with inference providers and model ecosystems such as AWS Bedrock, Azure OpenAI, OpenAI, Anthropic, Meta/Llama, and Mistral, along with orchestration frameworks such as LangChain, LlamaIndex, MCP, or comparable approaches.
Cloud and infrastructure: Experience with cloud platforms such as AWS, Azure, or GCP; Docker, Kubernetes, Terraform, CI/CD, observability tools, and production... For full info follow application link.

## Description

We're a global, multi-disciplinary team that's putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive, we give you the keys to fast-track your career.
Engineer audio systems and integrated technology platforms that augment the driving experience
Combine ingenuity, in-depth research, and a spirit of collaboration with design and engineering excellence
Advance in-vehicle infotainment, safety, efficiency, and enjoyment
About the Role
Drive hands-on delivery of AI and Generative AI solutions for Digital HR and HR Business Partners. You will combine full-stack AI development with strong HR process, data, privacy, and governance awareness to solve business problems across the employee lifecycle, workforce planning, skills intelligence, talent, learning, case management, and employee experience.

This role is not centered on configuring one HR platform. Instead, you will evaluate AI capabilities across tools and vendors, advise HR stakeholders on where AI can create value, and build practical solutions when custom development, orchestration, or integration is the right path. You will architect, develop, and maintain production-grade systems that may include RAG pipelines, agentic workflows, model routing, vector search, evaluation, guardrails, observability, analytics, and visualizations integrated with enterprise HR data products and internal platforms.
What You Will Do
Solve HR business problems with AI: Partner with Digital HR, HR COEs, HRIS, IT, Legal, Privacy, and regional stakeholders to understand business needs and identify where AI can automate work, generate insight, or improve decision support.
Act as a trusted AI consultant: Advise HR teams on AI opportunities, risks, implementation options, data readiness, governance requirements, and the trade-offs between vendor capabilities, configuration, integration, and custom development.
Build AI-enabled HR solutions end to end: Develop prototypes and production solutions such as HR knowledge copilots, employee policy assistants, case triage tools, document summarization, onboarding support, skills intelligence, workforce planning analytics, and AI-assisted process workflows.
Evaluate AI tools vendor-neutrally: Assess capabilities across HR and enterprise platforms such as Workday, ServiceNow, Microsoft, and emerging AI tools, focusing on concepts, fit, value, and feasibility rather than deep specialization in one system.
Design and implement RAG pipelines: Build retrieval solutions over HR policies, job profiles, skills taxonomies, learning content, business rules, case data, requirements documents, lessons learned, and other structured or unstructured HR content.
Develop agentic workflows: Use orchestration frameworks and agent patterns to translate HR processes into reliable AI-enabled workflows with appropriate human review, escalation, and auditability.
Create analytics and visualizations: Move beyond static reporting by developing AI-driven insight generation, workforce skill heat maps, automation and augmentation analysis, replacement-impact views, and decision-support tools from integrated HR data products.
Implement enterprise-grade controls: Build guardrails, content policies, safety filters, prompt/version management, model evaluation, latency and throughput tuning, cost controls, fallback strategies, and model-routing approaches.
Protect HR data: Design solutions with privacy, PII protection, role-based access, employee-data sensitivity, works council considerations, retention requirements, and model/data governance built in from the start.
Operate production solutions: Containerize applications, automate CI/CD, monitor usage and quality, debug production issues, manage observability, and improve cost, reliability, and performance over time.
Communicate clearly and iterate quickly: Translate complex AI concepts for non-technical HR stakeholders, document recommendations, share demos, gather feedback, and build trust through practical value delivery.


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