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Lead Software Engineer- Cable Backplane Systems

Job

Amphenol TCS

Valley Green, PA (In Person)

Full-Time

Posted 3 weeks ago (Updated 2 weeks ago) • Actively hiring

Expires 5/28/2026

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Job Description

Title:
Lead Software Engineer- Cable Backplane Systems Location:
Valley Green, PA; Nashua, NH; Raleigh, NC; Austin, TX Amphenol High Speed Products Group is the market leader for high speed, high bandwidth electrical connectors for the Telecom/Datacom market (Mobile Networks, Storage, Servers, Routers, Switches, etc.). Our products enable the electronics revolution and remain a key enabler for major Tier 1 OEMs globally. Headquartered in Nashua, NH, we operate design, sales, and manufacturing facilities worldwide. We are expanding our software team and are seeking a Lead Software Engineer for Cable Backplane Systems to drive the architecture and development of next-generation data platforms powering AI-driven datacenters. In this role, you will lead the design and implementation of scalable software systems that connect factory test data, manufacturing systems, and engineering workflows. You will operate at the intersection of software engineering, data engineering, and applied analytics, while mentoring engineers and shaping technical direction. This is a high-impact leadership role with opportunities to incorporate AI/ML techniques to improve factory efficiency, product quality, and engineering insights.
Responsibilities:
Technical Leadership & Strategy:
Lead the design, architecture, and evolution of scalable data platforms supporting factory and engineering systems Define technical standards, best practices, and long-term system architecture Mentor and guide software engineers through design reviews, code reviews, and career development Drive cross-functional alignment between software, manufacturing, test, and engineering teams Identify and implement opportunities for innovation, including AI/ML adoption
Data & Platform Engineering:
Architect, implement, and optimize large-scale databases and data pipelines Ensure high data integrity, traceability, and performance across high-volume environments Define data models, schemas, and governance strategies to support analytics and reporting Oversee integration of data from MES, lab equipment, and engineering design systems
Factory & Engineering Integration:
Partner with factory, test, and engineering stakeholders to define data requirements and system capabilities Lead development of APIs and services enabling reliable, scalable data exchange Drive automation of test data collection, analysis, and reporting systems Ensure seamless integration between manufacturing and engineering workflows
Analytics & AI Enablement:
Lead development of infrastructure supporting advanced analytics and AI/ML workflows Champion the use of AI for yield optimization, predictive analytics, and process improvement Collaborate with domain experts to deliver data-driven tools that enhance decision-making Promote a data-centric culture across engineering and manufacturing teams
Qualifications:
BS in Computer Science, Computer Engineering, or related field (MS preferred) 8+ years of experience in software engineering, with demonstrated technical leadership Strong experience designing and scaling large data platforms, databases, and pipelines Experience with data analytics, statistics, and/or machine learning workflows Proven ability to lead projects and mentor engineers in a collaborative environment Experience building APIs, distributed systems, and data integration solutions Familiarity with data visualization, dashboards, and reporting tools Experience working in cross-functional, multi-disciplinary engineering teams Strong hands-on experience with source control, code reviews, and CI/CD practices Excellent communication skills with the ability to influence technical and non-technical stakeholders Self-driven, adaptable leader who thrives in ambiguous environments and drives clarity and execution Preferred Qualifications Experience in manufacturing, factory systems, or test automation environments Familiarity with AI/ML frameworks and deploying models in production environments Experience working with high-speed systems, hardware interfaces, or electronics manufacturing

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