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# Technical Architect

- **Company:** HCLTech
- **Location:** Coventry, UK
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Machine Learning, Natural Language Processing, Large Language Models, Generative AI
- **Published:** June 22, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=b14b80d19ab53f4c

## About the Role

Do you have experience in Natural language processing?, Proven track record as a Product Manager in a digital environment, preferably within a client-facing or consulting context.
Excellent communication skills with the ability to engage, influence, and manage a diverse set of stakeholders.
Strong product mindset with a focus on problem-solving, value creation, and a willingness to challenge the status quo.
Solid understanding of automation, workflow optimisation, and process re-engineering.
Ability to simplify and communicate complex concepts, including AI/ML, in a clear and accessible manner.
Other Requirements

Desirable

Experience within the Energy & Utilities sector.
Strong understanding of AI technologies relevant to utilities, including LLMs, NLP, summarisation techniques, Retrieval-Augmented Generation (RAG), and traditional machine learning approaches.
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## Description

Define and drive product vision, strategy, and roadmap for AI solutions, grounded in user needs, business value, and technical feasibility.
Lead and/or support backlog creation, refinement, prioritisation, and feature definition to ensure continuous value delivery.
Establish, track, and communicate clear success metrics and product KPIs, including developing financial models to demonstrate ROI and business impact.
Facilitate workshops and alignment sessions to help stakeholders understand trade-offs and make informed decisions.
Translate complex or ambiguous business requirements into clear, outcome-focused user stories, supported by data and experimentation frameworks.
Collaborate closely with engineering, architecture, and delivery teams to identify, validate, and deliver AI-enabled opportunities across the product lifecycle.
Lead multidisciplinary teams (pods), fostering focus, alignment, and high-quality execution of AI use cases.
Create clear and compelling communication materials, ranging from executive-level reports to detailed delivery updates.


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