TE Connectivity
Website:
te.com
Job details:
At TE, you will unleash your potential working with people from diverse backgrounds and industries to create a safer, sustainable and more connected world.
Job Overview
This is a hands-on technical role responsible for designing, building, and deploying AI solutions directly from business requirements across strategy, product management, business development, sales, and marketing.
This role focuses on applied, outcome-driven AI — rapid experimentation, practical deployment, and measurable business impact. The engineer works closely with non-technical stakeholders to translate ambiguous problems into usable AI-powered tools and workflows, iterating quickly based on real-world feedback.
Roles And Responsibilities
Solution Design & Development
- Design and build applied AI solutions (ML and GenAI) based on business requirements
- Develop end-to-end AI workflows, including data ingestion, modeling, prompt engineering, orchestration, and output delivery
- Rapidly prototype proofs-of-value and evolve them into deployable solutions
- Integrate AI capabilities into existing enterprise tools and workflows (e.g., CRM, analytics platforms, internal applications)
Business Partnership
- Work directly with Strategy, Product, Sales, Marketing, and BD teams to clarify problems and define AI-enabled solutions
- Translate loosely defined business needs into technical approaches and working solutions
- Act as a technical thought partner, advising what is feasible, scalable, and worth pursuing
Experimentation & Iteration
- Operate in a fast-paced, experimental environment with short build-test-learn cycles
- Iterate solutions based on user feedback, adoption data, and business outcomes
- Balance speed and pragmatism with appropriate technical rigor and governance
Deployment & Enablement
- Support deployment of AI solutions into production environments (with IT/data partners as needed)
- Document solutions and enable business users to effectively adopt and use AI tools
- Contribute to reusable components, patterns, and best practices for applied AI
Qualifications
Technical Skills
- Strong proficiency in Python
- Hands-on experience with machine learning
- Experience working with LLMs, prompt engineering, RAG architectures, or AI agents
- Familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
- Experience integrating APIs and working with data pipelines
- Ability to prototype quickly using modern AI tooling and cloud-based services
Business & Collaboration Skills
- Ability to work directly with non-technical stakeholders
- Strong problem-framing and requirement translation skills
- Clear communication of technical concepts to business audiences
- Comfort operating with incomplete information and evolving requirements
Preferred Qualifications
- Experience building AI solutions for commercial, marketing, operations, or product use cases
- Exposure to enterprise data environments and systems
- Experience deploying AI solutions beyond proof-of-concept
- Familiarity with AI governance, data privacy, and responsible AI practices
Success Measures
- Speed from idea to working solution
- Adoption and sustained use of AI solutions by business teams
- Demonstrated business impact (e.g., revenue enablement, efficiency gains, decision quality)
- Ability to independently deliver applied AI solutions
Click on Apply to know more.