AI Principal Data Engineer

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.

About the Role

As the AI Principal Data Engineer, you will lead the architecture and development of end-to-end data platforms for agentic AI training, evaluation, and reinforcement.  You will play a pivotal role in defining and driving the overall AI data platform and strategy for our automotive electronics manufacturing organization. You will oversee and align the efforts of our AI data platform, to ensure that the AI data platform supports business objectives, enhances operational efficiency, and enables innovation.

What You Will Do

• Lead the architecture and development of end-to-end data platforms for agentic AI training, evaluation, and reinforcement in alignment with business goals, technology strategy, budget, resource skill sets and availability.

• Build and manage scalable, real-time pipelines to ingest, transform, and store multimodal data (text, logs, user interactions, actions, environments.)  Design dynamic memory and knowledge storage systems for agents (vector stores, graph DBs, memory stores).

• Collaborate with AI/ML researchers to integrate live feedback, human-in-the-loop data, and auto-labeling systems into pipelines.

• Build industry connects, partner ecosystems to deliver Harman use cases. Embed in research communities, onboard best practices, scalable architecture to Harman.

• Document and communicate project deliverables and technical information in status meetings with internal stakeholders.

• Own data governance, quality, and security policies, especially in the context of self-improving and self-refining AI agents, coordinating with global data security on overall alignment with global policies & standards.

• Build metadata tracking and observability tools for agent behavior and decision paths (data lineage, reproducibility, versioning).

• Mentor junior data engineers and contribute to a high-performance engineering culture.

• Stay ahead of cutting-edge trends in agentic AI infrastructure and incorporate them into the roadmap.

• Incorporate understanding of the company, processes and partners along with our key business drivers into the data engineering framework.

• Serve as subject matter expert and advisor on AI data engineering, technology trends, and emerging solutions for discussions within the organization as well as external partners, customers and vendors.

What You Need

• Graduate degree in computer science, engineering, or a related field (PhD a plus).

• 6+ years of experience in data engineering, including at least 2 years in a leadership or architect role.

• Advanced engineering and conceptual knowledge in data engineering and its implementation patterns using Matillion, Snowflake & MS Fabric.

• Strong programming expertise in Python and SQL

• Deep experience with real-time streaming frameworks (Kafka, Pulsar, Spark Streaming, Flink)

• Proficient in building and maintaining data lakes and warehouses (e.g., Snowflake, Delta Lake, BigQuery, MS Fabric)

• Experience with LLMs, vector databases (Pinecone, FAISS), and agent memory systems.

• Strong knowledge of MLOps or agent lifecycle tooling (e.g., LangChain, MCP, AutoGen, MLflow)

• Experience in cloud-native data architecture (AWS/GCP/Azure), incl. orchestration (e.g. Airflow, dbt)

• Ability to influence and drive change within and outside of your sphere of control.

• Excellent communication and leadership skills with the ability to influence stakeholders.

What is Nice to Have

• Experience in Databricks or other alternative data engineering frameworks.

• Experience with functional/streaming paradigms, reinforcement learning environments, fine-tuning pipelines, or multi-agent systems.

• Familiarity with agent frameworks (e.g., OpenAI Assistants, LangGraph, AutoGPT, CrewAI, Semantic Kernel).

• Data Engineering certification, e.g. DP-600 for MS Fabric.

• Project Management certification, e.g. PMI certification.

• Possess advanced skills in cross-cultural awareness, leadership, influence, communication, problem solving, negotiation, and conflict resolution.

• Knowledge of the automotive and manufacturing industries is a plus.