Lead execution of Product Engineering AI and automation initiatives across photonics products. Build and deploy reusable AI/automation tools, transform engineering data into AI-ready systems, and drive cross-functional adoption to improve development, qualification, manufacturing, and reliability processes.
Product Engineering develops and establishes many of the processes used throughout product development, qualification, and manufacturing. As product complexity, engineering data, and production volumes continue to grow, these processes must evolve into connected, traceable, and AI-ready systems.
The Photonic Product Engineer for AI & Automation is responsible for executing Product Engineering's AI and automation initiatives and driving adoption across the organization. The role works closely with Development, Product Engineering, Test, Reliability, Quality, Operations, Manufacturing, and IT teams to establish common methods, reusable tools, and scalable practices that improve engineering effectiveness and support future growth.
Success in this role is measured not only by technical solutions delivered, but by the extent to which AI, automation, and data-driven methods become embedded within everyday engineering practice.
The position is based in Sunnyvale, Ca.
- Execute Product Engineering AI and automation initiatives across PIC, ASIC, TROSA, and Plug.
- Drive adoption of AI, ML, automation, and data-driven engineering practices within Prod Eng and partner organizations.
- Establish common methods, frameworks, and knowledge systems that enable scalable use of AI across the product lifecycle.
- Transform engineering data, workflows, and traceability into AI-ready systems spanning development, qualification, manufacturing, reliability, and field performance.
- Build, validate, and deploy reusable tools, agents, analytics, and automation solutions that improve engineering effectiveness.
- Partner with Development, Test, Reliability, Quality, Manufacturing, Operations, and IT teams to align data, tools, and practices and deliver measurable business impact.
- PhD in Electrical Engineering, Computer Science, Data Science, Physics, Photonics, Applied Mathematics, or related field.
- Experience applying AI, machine learning, analytics, software, or automation to engineering, product development, test, or manufacturing challenges.
- Strong programming, data analysis, and tool development skills using Python or similar technologies.
- Experience with AI technologies, engineering data systems, knowledge management, traceability, or decision-support tools.
- Experience with optical transceiver products, photonics, DSP, semiconductor technologies, Product Engineering processes, or manufacturing and test systems is highly desirable.
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Build and maintain Databricks datasets, SQL/Python analytical workflows, and governed semantic layers. Support AI agent enablement by curating knowledge, prompts, and metadata. Partner with business stakeholders to deliver insights, automate workflows, and ensure data governance, quality, and trusted metrics for self-service intelligence and executive reporting.
Top Skills:
Azure OpenaiChatgptDatabricksDatabricks GenieGenerative AiGenie SpacesMicrosoft CopilotPrompt EngineeringPythonSQLUnity Catalog
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Perform complex analyses of large healthcare claims datasets to support Payment Integrity operations. Design, validate, and maintain production queries, reports, dashboards, and KPI frameworks. Lead root-cause analysis, data validation, and forecasting. Partner with business and technical stakeholders to translate requirements, monitor data quality and algorithm performance, and deliver actionable recommendations to improve operational outcomes and compliance.
Top Skills:
ExcelFacetsIsysOracleQnxtSnowflakeSQLSQL Server
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Support CXR impact reporting by gathering stakeholder requirements, preparing pre/post impact analyses, building BI tools and dashboards, cleaning and normalizing large structured datasets, performing descriptive and regression analytics, and presenting actionable insights to stakeholders.
Top Skills:
D3JsDatabricksExcelPower BISnowflakeSQLTableau
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
