Principal Engineer - Supply Chain AI Solutions

HARMAN International • Novi, MI

16d • $125,250 - $183,700 • Hybrid

About The Position

Drive hands-on delivery of AI and Generative AI solutions that streamline supply chain workflows and deliver measurable business value through hours saved, cycle-time reduction, improved decision quality, risk mitigation, and the breadth of users served. You will architect, develop, and maintain production-grade systems encompassing RAG pipelines, agentic tools, model routing, vector search, evaluation and guardrails, and observability, all tightly integrated with internal platforms, enterprise datasets, and supply chain systems. This is primarily a hands-on GenAI and software engineering role, with supply chain expertise providing the domain context for solution design and delivery.

Requirements

• 8+ years of experience building production software, ideally including ML systems and hands-on work with LLMs and Generative AI; demonstrated technical leadership while remaining deeply hands-on.
• Programming: Python (FastAPI, NumPy, Pandas, scikit-learn, Pydantic, Jinja2) and Node.js; strong proficiency with APIs and distributed systems.
• LLMs and Frameworks: Hands-on experience with at least one major deep learning or LLM stack, such as PyTorch/Transformers or TensorFlow/Keras, and orchestration frameworks such as LangChain or LlamaIndex.
• Model Providers: Working familiarity connecting to inference providers and model ecosystems such as AWS Bedrock, OpenAI, Anthropic, Meta/Llama, and Mistral.
• Data and Storage: SQL and NoSQL databases (PostgreSQL, DynamoDB), Elasticsearch for search and analytics, and vector databases (Pinecone, Weaviate, FAISS, Milvus, pgvector).
• Cloud and Infrastructure: AWS (S3, EC2, Lambda, CloudWatch, Fargate, EKS/ECS), Azure, GCP, Databricks, Docker, Kubernetes, Terraform, CI/CD, Airflow, and Kafka.
• Enterprise Integration: Demonstrated experience integrating production software or AI systems with one or more enterprise platforms using APIs, event-driven interfaces, batch or data pipelines, authentication and authorization, and robust error-handling patterns.
• Operational Excellence: Load balancing, monitoring and alerting (Datadog, Grafana, LangFuse), debugging production issues, evaluation and release discipline, and cost and performance optimization.
• Soft Skills: Strong communication abilities, product-oriented thinking, effective collaboration with technical and functional subject-matter experts, and the capacity to learn and adapt quickly in a dynamic environment.
• BS, MS, or PhD in Computer Science, Electrical Engineering, Mathematics, or equivalent professional experience.

Nice To Haves

• Preferred Platform Experience - Strong Plus: Experience with one or more of SAP, SAP S/4HANA, SAP Ariba, enterprise resource planning (ERP) platforms, Ivalua, OneStream, Darwin Analytics, SupplyOn, or SAP Integrated Business Planning (IBP). Experience using or extending platform-native AI capabilities is valuable; breadth across every platform is not required.
• Preferred Supply Chain Domain Experience - Strong Plus: Delivery experience in one or more of procurement, supplier collaboration and management, risk management, quality, costing, engineering, materials and warehouse management, finished-goods or component-level planning, and ESG. Familiarity with automotive supply chain and compliance concepts such as Extended Producer Responsibility (EPR), Process Release Audit (PRA), and Production Part Approval Process (PPAP) is an additional advantage.

Responsibilities

• Automate high-impact supply chain workflows for internal stakeholders, prioritizing initiatives with the greatest time savings, business impact, and user reach.
• Deliver production-ready copilots and applications for knowledge search, document summarization, intelligent recommendations, conversational analytics, exception management, and end-to-end workflow automation.
• Apply GenAI and software engineering to supply chain use cases across procurement; supplier collaboration and management; risk management; quality; costing; engineering; materials and warehouse management; finished-goods and component-level planning; and ESG.
• Architect and develop scalable, high-performance data and AI systems that support RAG, agentic workflows, secure tool use, and model orchestration.
• Own the complete solution lifecycle, from problem definition and rapid prototyping through rigorous evaluation, production deployment, ongoing monitoring, and continuous improvement.
• Design and implement RAG pipelines over heterogeneous and often messy enterprise and supply chain data, including contracts, purchase orders, supplier documents, bills of material, requirements, quality records, audit artifacts, planning data, business rules, and unstructured content. Select embedding strategies, chunking approaches, vector search configurations, rerankers, metadata or knowledge-graph enrichment techniques, and routing policies to maximize retrieval quality.
• Develop agentic workflows leveraging LangChain, LlamaIndex, Model Context Protocol (MCP), and agent-to-agent (A2A) protocols; build secure tools that allow agents to retrieve data and execute approved actions in enterprise systems.
• Integrate AI solutions with enterprise applications and data platforms through APIs, events, batch pipelines, and governed access patterns; design integrations that are resilient, observable, and maintainable.
• Evaluate when to use platform-native embedded AI capabilities versus custom-built GenAI components, and design modular solutions that can evolve with the enterprise tool landscape.
• Translate subject-matter-expert knowledge into robust prompts, tools, workflow logic, and validation rules; evaluate trade-offs among prompt engineering, retrieval augmentation, fine-tuning, and deterministic software.
• Work hands-on with large language models, vector databases such as Pinecone and FAISS, and agent memory systems.
• Establish operational excellence through rigorous SLAs; safety and guardrail mechanisms; prompt and version management; transparent evaluation; latency and throughput optimization; cost controls; load balancing; fallback or model-routing strategies; and human review for process-critical decisions.
• Establish observability using tools such as Datadog, Grafana, and LangFuse, along with model and data governance, access controls, auditability, and operational support appropriate for internal enterprise environments.
• Build and maintain data products, lakes, and warehouses using platforms such as Snowflake, Delta Lake, BigQuery, and Microsoft Fabric to support supply chain AI use cases.
• Build internal copilots and customer-facing features using React, Node.js, and Python with REST or GraphQL backends; containerize applications with Docker, orchestrate with Kubernetes, automate CI/CD pipelines, and manage infrastructure as code using tools such as Terraform.
• Collaborate closely with supply chain subject-matter experts, requirements, testing, validation, cybersecurity, data, platform, and enterprise application teams; communicate proactively and iterate rapidly in a fast-paced environment.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Principal