Principal Engineer - HR AI Solutions

About the role

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.

Responsibilities

• 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.

Requirements

• 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 support practices.
• HR domain awareness: Understanding of HR data, employee lifecycle processes, people analytics, skills and job architecture, talent and learning processes, case management, workforce planning, and the sensitivity of employee information.
• Governance mindset: Ability to design for privacy, PII protection, role-based access, auditability, human-in-the-loop review, regulatory considerations, works council approvals, and enterprise model/data governance.
• Consulting and communication: Strong business-problem framing, product-oriented thinking, stakeholder facilitation, clear communication, and the ability to explain AI options to HR leaders and subject-matter experts.

Qualifications

• Education: BS, MS, or PhD in Computer Science, Data Science, Electrical Engineering, Mathematics, Human Resources Technology, or equivalent professional experience.
• Preferred Experience: Experience developing AI solutions for HR, people analytics, talent, learning, recruiting, employee experience, HR service delivery, or workforce planning use cases.
• Familiarity with HR and enterprise AI platforms such as Sana AI, Workday, ServiceNow HRSD, SAP SuccessFactors, or Microsoft 365/Copilot ecosystems; platform-specific configuration experience is helpful but not required.
• Experience creating skills intelligence, workforce planning, automation-potential analysis, or organizational heat-map visualizations.
• Experience working with Legal, Privacy, Information Security, Works Councils, or equivalent governance bodies on employee-data solutions.

Skills

• Strong conceptual and practical understanding of LLMs, embeddings, RAG, agentic workflows, prompt engineering, model orchestration, model evaluation, guardrails, and responsible AI practices.
• 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.
• 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.
• 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.
• 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.
• Experience with cloud platforms such as AWS, Azure, or GCP; Docker, Kubernetes, Terraform, CI/CD, observability tools, and production support practices.
• Understanding of HR data, employee lifecycle processes, people analytics, skills and job architecture, talent and learning processes, case management, workforce planning, and the sensitivity of employee information.
• Ability to design for privacy, PII protection, role-based access, auditability, human-in-the-loop review, regulatory considerations, works council approvals, and enterprise model/data governance.
• Strong business-problem framing, product-oriented thinking, stakeholder facilitation, clear communication, and the ability to explain AI options to HR leaders and subject-matter experts.

Benefits

• Access to employee discounts on world-class products (JBL, HARMAN Kardon, AKG, and more).
• Extensive training opportunities through our own HARMAN University.
• Competitive wellness benefits.
• Tuition reimbursement.
• "Be Brilliant" employee recognition and rewards program.
• An inclusive and diverse work environment that fosters and encourages professional and personal development.

Pay

$ 125,250 - $ 183,700 Dependent on the position offered, other forms of compensation are also available, such as bonuses or commission. Pay is based on a wide range of factors, including, without limitation, skill set, experience, training, location, and business need.

Schedule

Ability to work from an office in Novi, MI, 3+ days per week (hybrid).

Application Instructions

Please apply directly through the provided link or email your resume to [email protected]