We are looking for an AI Engineer to help design, build and operate AI-enabled internal products and platforms across National Grid.
This is a hands-on senior engineering role for someone who can move confidently between modern web application development and applied AI engineering. The role is not focused solely on model development or experimentation. It is responsible for turning AI capabilities into secure, maintainable and production-ready products that solve real organisational problems.
An immediate focus is the Strategic Review platform: National Grid's internal tool for programme visibility, strategic initiative tracking and executive-level data storytelling. The platform includes a Connections Dashboard moving toward production, a financial reporting capability being scoped, and an evolving AI layer supporting analysis and conversational access to underlying data.
The AI Engineer will develop this AI layer and the wider product capabilities around it. This includes building chat interfaces, agentic workflows, tool integrations, structured outputs, retrieval and grounding mechanisms, evaluation frameworks, observability, and appropriate human-in-the-loop controls.
The role requires strong experience with TypeScript, React and modern full-stack web development. Experience with the Vercel AI SDK is particularly valuable, including streaming interfaces, tool calling and agent orchestration. Payload CMS experience is a significant advantage because it is used extensively across the platform.
This role is for someone who can operate with senior autonomy: understanding ambiguous requirements, shaping sound technical approaches, delivering high-quality software and working closely with product, design, data, architecture and security teams to take AI products from proof of concept into production.
Key Accountabilities
AI Product Development
- Design and develop full-stack AI applications using TypeScript, React, and modern web technologies.
- Build conversational interfaces with streaming responses, intuitive user experiences, and robust error handling.
- Develop AI solutions using frameworks such as Vercel AI SDK, LangGraph, LangChain, or similar platforms.
- Translate business requirements into scalable, maintainable technical solutions.
- Create reusable patterns for AI chat, workflow automation, content generation, and analytics.
- Integrate AI capabilities into existing products and business processes.
- Ensure high standards of performance, security, accessibility, maintainability, and code quality.
Agentic Systems & Conversational AI
- Design and implement AI agents capable of multi-step reasoning, tool selection, and workflow execution.
- Develop integrations with enterprise applications, APIs, and approved data sources.
- Define agent state, memory, context management, validation rules, retry logic, and failure handling.
- Implement human-in-the-loop approval processes for sensitive or high-impact actions.
- Ensure transparency through source attribution, execution tracking, and auditability.
AI Quality, Evaluation & Observability
- Develop evaluation frameworks, test datasets, and quality metrics for AI features.
- Monitor answer quality, groundedness, tool usage, latency, output accuracy, and operational cost.
- Implement logging, tracing, monitoring, and observability capabilities for AI workflows.
- Continuously improve prompts, models, tools, and workflows through data-driven feedback.
- Manage prompts, model configurations, and evaluation criteria as version-controlled assets.
Data & Integration
- Integrate AI capabilities with structured and unstructured enterprise data sources.
- Implement retrieval, grounding, and context-engineering strategies to improve response quality.
- Build secure integrations with APIs, content management systems, data platforms, and business applications.
- Ensure compliance with data security, authorization, governance, and audit requirements.
- Support source attribution, data lineage, and information freshness controls.
Engineering & Delivery
- Write clean, tested, maintainable code following established engineering standards.
- Participate in architecture reviews, technical design discussions, and code reviews.
- Implement automated testing across applications, integrations, and AI workflows.
- Support continuous delivery while managing technical debt and maintaining enterprise standards.
- Establish best practices for AI-assisted development tools, including GitHub Copilot, Claude Code, and related platforms.
Collaboration & Leadership
- Partner with Product, Design, Architecture, Security, Data, and Engineering teams.
- Provide technical expertise throughout discovery, design, development, testing, deployment, and adoption.
- Communicate technical recommendations, trade-offs, and risks to stakeholders.
- Mentor engineers and contribute to AI engineering standards and best practices.
- Help establish scalable frameworks for enterprise AI product delivery.
Qualifications
- Proven experience as a senior Software Engineer, AI Engineer, Full-Stack Engineer or equivalent, delivering complex digital products.
- Strong professional experience with TypeScript and React.
- Experience building modern full-stack web applications using frameworks such as Next.js.
- Practical experience building AI-enabled product features, not only isolated model experiments or notebooks.
- Experience with the Vercel AI SDK or comparable AI application frameworks.
- Experience building conversational or chatbot interfaces, including streaming responses and interaction-state management.
- Understanding of agentic systems, tool calling, structured outputs and multi-step AI workflows.
- Experience integrating large language models with application data and external services.
- Ability to design clear boundaries between deterministic code and model-driven behaviour.
- Strong understanding of API design, authentication, authorisation and secure data handling.
- Experience testing and debugging asynchronous, distributed or integration-heavy application behaviour.
- Understanding of AI evaluation, observability, grounding and common failure modes.
- Ability to translate ambiguous product requirements into sound technical designs and working software.
- Strong engineering judgement, including the ability to balance delivery speed with maintainability and operational risk.
- Comfortable working in a fast-moving, cross-functional team where product, design and engineering decisions are made collaboratively.
- Clear written and verbal communication with both technical and non-technical audiences.
- High degree of autonomy and ownership from discovery through production support.
National Grid
40 Sylvan Rd
Waltham
Massachusetts United States
www.nationalgridus.com
