Principal Engineer, AI

About the role

Drive hands-on delivery of AI and Generative AI solutions that streamline workflows and deliver measurable business value-measured by hours saved and the breadth of users served. You will architect, develop, and maintain production-gra de systems encompassing RAG pipelines, agentic tools, model routing, vector search, evaluation, and guardrails, and o bservability-a ll tightly integrated with internal platforms and enterprise datasets.

Responsibilities

• Automate high-impact workflows for internal stakeholders, prioritizing initiatives with the greatest time savings and broadest user reach.
• Deliver production-rea dy copilots and customer-facin g applications for knowledge search, document summarization, intelligent recommendation s, conversational analytics, and end-to-end workflow automation.
• Establish operational excellence through rigorous SLAs, latency and throughput optimization, robust safety and guardrail mechanisms, transparent evaluation frameworks, and cost-efficient inference strategies.
• Architect and develop scalable, high-performan ce data and AI systems that support GenAI use cases including RAG, agentic workflows, and model orchestration.
• Own the complete solution lifecycle: problem definition → rapid prototyping → rigorous evaluation → production deployment → ongoing monitoring.
• Implement guardrails (content policies, safety filters), prompt and version management, latency and throughput tuning, cost controls, load balancing, and fallback or model-routing strategies.
• Design and implement RAG pipelines over heterogeneous and often messy datasets-inclu ding requirements documents, lessons learned, business rules, and unstructured content.
• Select appropriate embedding strategies, chunking approaches, vector search c onfigurations, rerankers, and routing policies to maximize retrieval quality.
• Develop agentic workflows leveraging LangChain, LlamaIndex, MCP, and agent-to-agent (A2A) protocols; build tooling for agentic coding use cases.
• Translate su bject-matter-e xpert knowledge into robust, maintainable prompts; evaluate trade-offs between fine-tuning and prompt engineering.
• Work hands-on with large language models, vector databases (Pinecone, FAISS), and agent memory systems.
• Containerize applications with Docker, orchestrate with Kubernetes, and automate CI/CD pipelines; manage infrastructure as code (e.g. Terraform).
• Establish observability (Datadog, Grafana, LangFuse), evaluation frameworks, and model/data governance and access controls appropriate for internal enterprise environments.
• Bring experience building and maintaining data lakes and warehouses (Snowflake, Delta Lake, BigQuery, MS Fabric).
• Build internal copilots and customer-facin g features using React, Node.js, and Python with REST or GraphQL backends.
• Collaborate closely with requirements, testing, validation, and platform teams; thrive in a fast-paced environment with clear, proactive communication and rapid iteration.
• What You Need To Be Successful
• 8+ years of experience building production software
• Programming: Python (FastAPI, NumPy, Pandas, scikit-learn, Pydantic, Jinja2) and Node.js; strong proficiency with APIs and distributed systems.
• Model Providers: Working familiarity with connecting to inference providers e.g. AWS Bedrock, along with OpenAI, Anthropic, Meta/Llama, and Mistral model ecosystems.
• Data & Storage: SQL and NoSQL databases (PostgreSQL, DynamoDB), Elasticsearch for search and analytics, and vector databases (Pinecone, Weaviate, FAISS, Milvus, pgvector).
• Cloud & Infrastructure: AWS (S3, EC2, Lambda, CloudWatch, Fargate, EKS/ECS), Azure, GCP, Databricks, Docker, Kubernetes, Terraform, CI/CD, Airflow, and Kafka.
• Operational Excellence: Load balancing, monitoring, and alerting (Datadog, Grafana, LangFuse), debugging production issues, and cost/performance optimization.
• Soft Skills: Strong communication abilities, product-oriented thinking, and the capacity to learn and adapt quickly in a dynamic environment.
• Education: BS, MS, or PhD in Computer Science, Electrical Engineering, Mathematics, or equivalent professional experience
• What Is Nice To Have
• Experience building ML Systems
• LLMs & Frameworks: Hands-on experience with at least one major deep learning or LLM stack (e.g., PyTorch/Transformers, TensorFlow/Keras) and orchestration frameworks such as LangChain or LlamaIndex.
• What Makes You Eligible
• Be willing to work in an office located in Novi, MI (hybrid)
• Successfully complete a background investigation and drug screen as a condition of employment
• What

Additional Information

A Career at HARMAN As a technology leader that is rapidly on the move, HARMAN is filled with people who are focused on making life better. Innovation, inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together, you'll discover that at HARMAN you can grow, make a difference and be proud of the work you do every day.

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