[Skip to main content](#main-content) [ OpenNash ](https://opennash.com/) / [Jobs](https://jobs.opennash.com/) [ 01 Search jobs](https://jobs.opennash.com/search/)[ 02 Companies](https://jobs.opennash.com/explore/)[ 03 Hiring report](https://jobs.opennash.com/reports/hiring/)[ 04 AI assistants](https://jobs.opennash.com/connect/)[ 05 How it works](https://jobs.opennash.com/methodology/) TE Connectivity · United States # Digital Engineer United States Operations Listed on TE Connectivity’s official careers site. Listed as of November 10, 2026. Check that it is still open and apply there. [Apply on TE Connectivity’s careers site →](https://careers.te.com/job/Digital-Engineer-NC-_/1447693000/) [OpenNash Jobs](https://jobs.opennash.com/) / [TE Connectivity](https://jobs.opennash.com/companies/te-connectivity/) / Digital Engineer ## Job description ### Job Overview TE Connectivity's Manufacturing & Process Development Engineering team is seeking a Digital Engineer to join the Central Engineering team, leading the development, justification, and deployment of AI and digital manufacturing solutions across the AD&M manufacturing network. This role is focused on developing practical AI solutions and deploying digital tools that improve engineering and manufacturing productivity. The engineer will link systems with machines and manufacturing processes – connecting equipment, test and inspection systems, and production data with MES, ERP, and analytics platforms – to enable real-time visibility, data-driven decisions, and scalable digital workflows. A strong focus on AI is central to the role. Candidates should demonstrate a genuine interest in AI and emerging digital technologies, with the curiosity and learning ability to rapidly build capability and turn new tools into practical manufacturing solutions. Proven AI expertise is valued, but learning agility and demonstrated application are equally important. The successful candidate will project manage digital deployments end to end, working with sites to identify opportunities, build business cases for digital integrations, and quantify savings based on deployment opportunities. ### A Lean mindset is essential processes should be simplified and stabilised before they are digitised. Strong communication skills are required. The engineer will actively align sites to the global digital deployment strategy, driving adoption of common standards and a “develop once, deploy many” approach across multiple locations. Due to the nature of the products and programmes supported, ITAR eligibility is preferred. Applicants who are a U.S. Person as defined by ITAR (22 CFR §120.62) will have access to the full range of programmes supported by the team. ### Eligibility ITAR U.S. Person (U.S. citizen, U.S. lawful permanent resident, or protected individual) preferred. Willing to travel 25%–50% domestically and internationally. ### Job Requirements AI Solutions Development Identify, develop, and deploy AI solutions for manufacturing and engineering use cases, including generative AI, AI agents, machine learning, and AI-enabled inspection. Develop and scale Manufacturing Engineering AI tools such as PFMEA generation, work instruction generation, troubleshooting assistants, and engineering knowledge management. Evaluate emerging AI technologies and platforms, and run structured pilots to prove value before scaling. Partner with IT, data, and AI teams to ensure solutions meet TE security, data governance, export-control, and responsible-AI requirements. Support AI adoption through training, user guidance, and AI champion networks at sites. Digital Tool Deployment & Site Rollouts Lead site-wide rollouts of digital tools, including deployment planning, user training, go-live support, and sustainment. Develop standard deployment packages (requirements, configuration, training, validation, and handover) that can be replicated across sites. Measure adoption and usage after go-live, and drive corrective actions where adoption or benefit falls short. Capture lessons learned and continuously improve the deployment approach. Systems Integration – Machines & Manufacturing Processes Link machines, automation, vision, and test systems with MES, ERP, databases, and analytics platforms. Define data requirements, connectivity architectures, and interfaces (e.g., OPC UA, MQTT, APIs, SQL) with site, IT, and OT teams. Enable real-time monitoring of OEE, process parameters, quality data, and traceability. Develop standard, secure, and scalable integration architectures aligned with TE IT/OT standards. Business Cases & Savings Development Work with sites to identify and prioritise digital integration opportunities based on value, readiness, and scalability. Build business cases and CER / investment justifications, quantifying labour, productivity, quality, capacity, and risk-reduction benefits and ROI. Build savings pipelines from deployment opportunities across sites and track realisation against approved business cases. Support supplier and platform evaluation, RFQs, and technical bid comparison for digital solutions. Project Management Manage digital projects from concept through deployment, including scope, plan, budget, resources, risks, and milestones. Coordinate site teams, IT, suppliers, and central engineering to deliver on time and to budget. Report project status, risks, and benefits to engineering and site leadership. Global Digital Strategy & Site Alignment Actively align sites to the global digital deployment strategy and roadmap. Promote common platforms, standards, and best demonstrated practices to avoid duplicated development across sites. Act as the link between central engineering and site teams, influencing without direct authority. Contribute to the AD&M digital manufacturing and AI roadmap. Lean Manufacturing & Continuous Improvement Apply Lean Manufacturing, Continuous Improvement, and TEOA principles to remove waste before digitising processes. Use process mapping and value stream analysis to target digital solutions where they deliver the greatest value. Support Kaizen events and standard work linked to digital deployments. What your background should look like Education Bachelor's Degree in Computer Science, Software, Data Science, Electrical, Manufacturing, Industrial, Automation, or Mechatronics Engineering, or a related discipline. ### Experience 5+ years of experience in manufacturing engineering, digital manufacturing, industrial software, automation, or data/analytics within a production environment. Demonstrated delivery of digital or technology projects from concept through deployment. Experience working with manufacturing sites and cross-functional teams across multiple locations. Experience building business cases or quantifying savings for technology investments. Demonstrated interest in AI, with evidence of self-directed learning or practical application. ### Preferred Qualifications Hands-on experience with generative AI, LLMs, AI agents, or machine learning applications. Experience with MES, IIoT, or manufacturing data platforms and machine connectivity. Programming or low-code experience (e.g., Python, SQL, Power Platform, Power BI). Experience in Aerospace, Defense, Medical, or other regulated manufacturing environments. Project management certification (e.g., PMP) or Lean Six Sigma Green Belt / TEOA training. Experience leading change management and multi-site rollouts. ### Technical Skills AI solution development: generative AI, prompt engineering, AI agents, machine learning fundamentals. ### Digital manufacturing MES, IIoT, OEE monitoring, digital work instructions, traceability. ### Systems integration OPC UA, MQTT, APIs, databases, ERP / MES interfaces. Data analytics and visualisation (e.g., Python, SQL, Power BI). Business case development, savings modelling, and ROI analysis. ### Project management planning, risk management, stakeholder reporting. ### Lean tools VSM, standard work, process mapping, Kaizen. ## At a glance - Posted by the employer: Not stated - First seen by OpenNash: Nov 10, 2026 - Last checked: Nov 10, 2026 - Listed for: Under a day - Location: United States[Apply on TE Connectivity’s careers site →](https://careers.te.com/job/Digital-Engineer-NC-_/1447693000/) ## Hiring at TE Connectivity - Open jobs: 3,005 - New in the last 7 days: After two weekly collections - Tracked since: Oct 13, 2026 [All TE Connectivity jobs](https://jobs.opennash.com/companies/te-connectivity/) · [Weekly hiring report](/reports/hiring/) ## More jobs at TE Connectivity ### [Electrical Engineer, MPDE](https://jobs.opennash.com/companies/te-connectivity/jobs/a51f1a716d50fc0c3258/) United States ### [Field Application Engineer II](https://jobs.opennash.com/companies/te-connectivity/jobs/6a6576a2e64904da7f94/) United States ### [MFG & Process DVL Engineer I](https://jobs.opennash.com/companies/te-connectivity/jobs/73073c3f9277a0c90053/) United States ### [MFG & Process DVL Engineer II](https://jobs.opennash.com/companies/te-connectivity/jobs/508530e12dd453e11351/) United States ### [Product Engineer II](https://jobs.opennash.com/companies/te-connectivity/jobs/0bf409f70deb21f0bae3/) United States ## Similar jobs at other companies ### [Silicon Test Engineer (Digital)](https://jobs.opennash.com/companies/qualcomm/jobs/465dd9e94c5f6e1bb6e1/) Qualcomm · Tijuana, Baja California, Mexico ### [Hardware Engineer Stf/ Digital Design](https://jobs.opennash.com/companies/lockheed-martin/jobs/f4e1a8002ca8a210de04/) Lockheed Martin · Owego, NY ### [Digital Factory Engineer](https://jobs.opennash.com/companies/eaton/jobs/ea7c78792d44d5fe9a5f/) Eaton · South Milwaukee, Wisconsin, USA ### [Staff Digital Design Engineer](https://jobs.opennash.com/companies/infineon-technologies/jobs/db28e77e2044629d3abd/) Infineon Technologies · San Jose, CA [Operations jobs](/functions/operations/) OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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