AI Product Manager – Manufacturing and Quality

Job Summary

We are hiring a

Technical AI Product Manager

to lead development of AI and GenAI products focused on

Manufacturing and Quality . You will work across product, ML, and engineering teams to build scalable, production-grade AI systems that improve operational efficiency, compliance, and product quality. This role requires deep technical fluency, structured product thinking, and end-to-end execution ownership.

Roles and Responsibilities

Own product lifecycle from problem framing to deployment and iteration

Define clear specs with data science and engineering for ML and GenAI solutions

Lead development of RAG pipelines, prompt orchestration, fine-tuning, and evaluation workflows

Balance model performance, latency, cost, scalability, and compliance constraints

Design API-first, modular, secure product architectures

Monitor product KPIs and drive iterative improvements

Prioritize across exploratory and scalable use cases

Stay current with AI / LLM tech and translate into product capabilities

Skills Required

Functional

Strong ownership with ability to structure ambiguous technical problems

Domain fluency across batch record review automation, GenAI for SOP interpretation, deviation summarization, predictive maintenance, and QA document generation

Experience working with plant ops, QA, and regulatory teams to define AI use cases with measurable impact on cycle time, compliance readiness, and process efficiency

Skilled at managing constraints around GxP, traceability, auditability, and secure deployment of AI products

Proven delivery of AI solutions in validated or regulated manufacturing environments

Technical

8+ years of experience in AI & Analytics for manufacturing & quality functions

Deep knowledge of LLMs, embeddings, vector stores, and RAG architectures

Hands-on with LangChain, Pinecone, OpenAI, Azure AI, Vertex AI or similar

Proficient in evaluating model metrics like top-k accuracy, latency, precision, recall

Comfortable reviewing code, writing specs, and using Git, Postman, Jupyter