Adam Whitehurst

Radiant is redefining how AI infrastructure is built. We design and operate AI-native infrastructure platforms engineered for sovereignty, performance, and scale — powering GPU-native workloads, multi-tenant control planes, and high-performance AI systems for the most demanding environments. We are building purpose-built AI infrastructure from powered land, to compute, to software. As we scale our operations and deploy capital into the next generation of AI infrastructure, we are looking to expand our product team with leaders who can combine technical strength with execution excellence and are driven to build. Radiant was established by Brookfield, a leading global alternative asset manager with over US$1 trillion of assets under management across real estate, infrastructure, renewable power and transition, private equity and credit. Brookfield's global relationships, investment expertise and access to long-term institutional capital provide Radiant with a differentiated platform from which to develop, finance and operate AI infrastructure assets. This combination of entrepreneurial execution and institutional sponsorship enables Radiant to pursue large-scale GPU and AI infrastructure opportunities globally. Job Summary: As a Senior Product Manager - Operations, you will own the strategy, roadmap, and delivery of Radiant’s internal tooling and integrations, helping teams operate and scale the cloud platform efficiently. You’ll work across CMDB, asset and service inventory, internal APIs, workflow automation, third-party integrations, and platform administration, partnering closely with engineering, SRE, infrastructure, networking, security, and operations. This is a highly technical product role focused on reducing operational friction, improving self-service, and creating reliable, scalable internal systems.   Key Responsibilities: Own the strategy, roadmap, and delivery of internal tooling, CMDB, service catalogues, operational workflows, and integrations. Translate business and operational needs into clear product requirements, specs, user stories, data models, and priorities. Partner with engineering to define solutions across APIs, integrations, automation, and platform tooling. Work with SRE, infrastructure, security, support, and other internal users to identify pain points and improve automation and self-service. Establish reliable sources of truth for infrastructure, services, customers, environments, ownership, and configuration. Drive prioritisation, backlog management, technical design discussions, delivery, and adoption. Define success metrics and ensure tooling is secure, observable, auditable, reliable, and well documented. Evaluate build vs. buy decisions and third-party tooling where appropriate. Qualifications: Experience owning technical products, internal platforms, developer tooling, or infrastructure products end-to-end. Experience working across data centre operations, hardware lifecycle and inventory, infrastructure support, field operations, or adjacent operational environments. Strong technical fluency across: APIs & integrations: REST, gRPC, webhooks, third-party APIs Infrastructure: Kubernetes, cloud platforms, containers, infrastructure-as-code Data & CMDB: relational modelling, inventory, ownership, dependency mapping Automation: queues, schedulers, workflow engines, event-driven systems Observability & security: logging, metrics, tracing, IAM, RBAC, audit logging Familiarity with tools such as NetBox, ServiceNow, Terraform, Grafana, Jira, or similar. Strong understanding of distributed systems concepts including retries, idempotency, eventual consistency, and failure handling. Strong prioritisation, communication, and stakeholder management skills. Comfortable working closely with engineers and making informed technical trade-offs without needing to be the primary implementer. Comfortable operating in a fast-paced environment and taking ambiguous problems from discovery through to delivery. What you bring: Systems thinking: Understand how infrastructure, services, data, and operational workflows fit together. Product thinking: Treat internal teams as customers and focus on measurable outcomes. Technical fluency: Able to work credibly across APIs, integrations, infrastructure, data, and architecture. Prioritisation: Balance operational pain, strategic value, technical complexity, and business impact. Ownership: Drive ambiguous problems from discovery and definition through to adoption and iteration.

Description   Senior Data and AI Architect Description Do you want to work to make Power for Good? We're the world's largest independent renewable energy company, guided by a simple yet powerful vision to create a future where everyone has access to affordable, zero carbon energy. We know that achieving our ambitions would be impossible without our people. Because we're tackling some of the world's toughest problems, we need the very best people to help us. They're our most important asset so that's why we continually invest in them. RES is a family with a diverse workforce, and we are dedicated to the personal and professional growth of our people, no matter what stage of their careers they're at. We can promise you rewarding work which makes a real impact, the chance to learn from inspiring colleagues from across a growing, global network and opportunities to grow personally and professionally. Our competitive package offers a wide range of benefits and rewards. Locations: UK - Kings Langley or Glasgow. Spain - Albacete or Madrid. Summary / Purpose of the Role Are you ready to architect the future of data and AI at one of the world's leading renewable energy businesses? At RES, we are looking for a Senior Data and AI Architect to design and build our next-generation Microsoft Fabric and Azure data estate, and to spearhead the engineering of the autonomous AI agents and intelligent services that operate within it. Reporting to the Head of Data and Analytics, you will own the forward-looking strategic and conceptual design of our global platform. This role combines elite enterprise data warehousing architecture with cutting-edge AI systems design. You will focus entirely on defining future-state architecture, establishing data standards optimized for LLM reasoning, and coding multi-agent orchestration frameworks. You will work in lockstep with our established Platform Operations team—who handle the day-to-day platform run, infrastructure maintenance, and legacy migrations—allowing you to serve as the ultimate technical authority for data and AI innovation across RES. Key Accountabilities Own Strategic Platform Direction: Define the target-state data and AI architecture, governance frameworks, and data modelling standards across Microsoft Fabric and Azure, aligned with global business goals. Design the Data-to-AI Interface: Establish how enterprise data is structurally modelled (using star schemas, semantic layers, dimensional modelling, and knowledge ontologies) to ensure autonomous AI agents can search, retrieve, and reason over data reliably without hallucinating. Pioneer Agentic AI Services: Lead the hands-on design, coding, and prototyping of multi-agent workflows and custom AI services; set rigorous automated evaluation frameworks, non-deterministic testing standards, and compliance gates. Set Engineering Standards & Code Patterns: Provide senior technical authority in Python, SQL, advanced software engineering, and LLM orchestration to the wider team. Review production code and build reusable code repositories to ensure quality engineering solutions. Drive Platform Capabilities: Identify, evaluate, and prototype emerging technologies and agentic tools (such as Model Context Protocol servers and vector databases), bringing highly automated new capabilities into our global data product portfolio. Architect Financial Efficiency: Design cloud data and AI patterns for optimal consumption efficiency, establishing best practices for token management, semantic caching, and compute cost optimization. Enforce Trust & Security by Design: Partner with Cyber Security and the Data & AI Governance Lead to ensure data privacy, access boundaries (RBAC), and prompt-injection defence mechanisms are embedded across all agents. Influence Global Leadership: Advise senior IT executives and business leaders on complex technical priorities, helping guide investment choices around data architecture, software engineering, and AI automation. Experience Required Enterprise Platform Design: 7+ years of demonstrated track record designing enterprise data architectures and data warehouses at scale to create organizational efficiency. Strategic & Conceptual Direction: Deep experience setting architectural reference designs, modeling standards, and technical direction across modern cloud data estates. Hands-on AI & Software Engineering: Proven, deep experience writing clean, modular code in Python, SQL, and consuming complex REST APIs. Must have hands-on experience building, testing, and deploying custom LLM agent frameworks (e.g., LangGraph, AutoGen, or LangChain) in production. Modern Cloud Data Tooling: Strong technical experience with Azure data and AI ecosystems (Azure AI Foundry, Microsoft Fabric, Azure AI Search) or equivalent components on alternative enterprise cloud platforms. Data Governance & Security Knowledge: Solid understanding of how data cataloging, lineage, and privacy compliance integrate with autonomous AI systems. Executive Communication & Leadership: Demonstrated ability to articulate complex technical strategies, lead workshops, run steering groups, and influence senior executive stakeholders. Exceptional Engineering Judgment: A proven track record of understanding the limitations of generative AI, demonstrating high judgment on where AI automation adds value versus where deterministic engineering must be used. Educational Foundation: Bachelor's degree in computer science, software engineering, data analytics, or equivalent deep, hands-on senior career experience. Why RES? A genuinely global remit: You will set the architecture and build the AI for a data platform used across a worldwide renewable energy business. Work at the intersection where data, analytics and AI meet: Your architecture and the agents you build will drive business outcomes across the globe in renewable energy. A modern, cloud-first stack: Azure, Fabric, Purview, MCP servers, and significant innovation investment. A collaborative, growing data and analytics function: Scope to shape how analytics and AI evolves for data and platforms. Join a brand new, agile team: Be at the heart of AI, innovation, Next Gen technology, and driving competitive advantage for RES. Agentic AI leadership: Set the blueprint for how RES builds and operates autonomous agents on our platform.

Lead Data Engineer Location: London | Full-time About LightWork AI LightWork AI is building the operating system for modern property management. Our platform, Felicity, is an intelligent AI assistant that automates the operational workload that slows down property managers, letting agents and build-to-rent teams. Felicity manages communications, compliance, maintenance coordination and scheduling — enabling property businesses to operate with the efficiency of modern digital platforms. The UK property management services industry is a £33B market undergoing a structural shift toward automation. Property teams currently spend up to 75% of their time on repetitive operational admin, and our AI is designed to automate up to 80–90% of these workflows. We are already live with pilot customers managing over 14,000 units, with overwhelmingly positive feedback and strong demand for the product as we scale toward revenue in 2026. LightWork AI is backed by experienced founders, industry advisors, and investors, and we are building toward a clear goal: to create the defining AI platform for property operations and build a unicorn company in the process. This is a rare opportunity to join early and own the data architecture of a fast-scaling AI company building the category-defining platform for property operations. The Role We are looking for a Lead Data Engineer to build and lead the data infrastructure powering LightWork AI’s platform. This role will architect and scale the systems that power our AI products — from real-time data pipelines and analytics infrastructure to vector databases and machine learning data workflows. You will work closely with AI engineers, backend engineers, and product teams to ensure our platform can process large volumes of operational data reliably and intelligently. As the first senior data hire, you will define our data architecture, tooling, and engineering standards, and play a key role in building the foundations of the future data team. Key Responsibilities ? Architect and build scalable data pipelines and infrastructure to support LightWork’s AI and product systems. ? Design and maintain data ingestion, transformation, and storage architectures for operational and AI workloads. ? Develop and manage batch and real-time data pipelines. ? Build and optimize systems for vector search, retrieval, and ML data pipelines. ? Ensure data reliability, security, and governance across the platform. ? Collaborate with AI and backend engineering teams to support training, inference, and product features. ? Implement monitoring, observability, and data quality frameworks. ? Optimize performance of large-scale datasets and query systems. ? Contribute to technical architecture decisions and long-term data strategy. ? Help build and mentor the future data engineering team as LightWork scales. Requirements Core Experience ? 7+ years of experience in data engineering or backend engineering roles. ? Strong experience designing and building data pipelines and distributed data systems. ? Experience working with relational databases (PostgreSQL preferred, but MySQL or similar is acceptable). ? Experience with NoSQL databases. ? Experience with vector databases used in modern AI systems. ? Strong programming experience in Python. Data & Infrastructure Experience with some of the following technologies is highly desirable: Frameworks / Infrastructure ? Apache Spark ? Apache Airflow ? Kafka ? Elasticsearch / OpenSearch Databases ? PostgreSQL ? MongoDB ? Vector databases such as Qdrant, Milvus, or pgvector Python Libraries ? Pandas ? Polars Engineering Skills ? Experience building scalable backend systems. ? Experience designing data models and storage architectures. ? Strong understanding of data processing performance and optimization. Nice to Have ? Experience with JavaScript / Node.js alongside Python. ? Experience working on AI or machine learning platforms. ? Familiarity with stream processing and event-driven architectures. ? Experience with cloud infrastructure (GCP, AWS, or Azure). ? Experience working in high-growth startups or early-stage companies. What We’re Looking For ? A high-ownership engineer who enjoys building systems from scratch. ? Someone excited to design the data backbone of an AI company. ? Strong problem-solving ability and architectural thinking. ? Comfortable working in a fast-moving startup environment. ? Motivated by the opportunity to build technology that transforms an entire industry. Why Join LightWork AI ? Build the data foundations of a category-defining AI company. ? Work directly with the founders and core engineering team. ? Join at an early stage with massive ownership and influence. ? Competitive salary + equity — share in the upside of what we build. ? Help create the AI infrastructure powering the future of property operations.