Data & AI Technical Lead

About TRG TRG is on a mission to make the world a safer place. We build AI and data fusion solutions that help government agencies and national security organisations connect intelligence from across domains - cyber, physical, financial, and location - and turn it into decisions that protect people. The work is meaningful, the problems are hard, and the impact is real. About the Role We're looking for a Data & AI Technical Lead to work closely with our Principal Data Engineer - taking ownership of technical design and architecture across data and AI systems, and acting as a reliable force multiplier for the team. This is a hands-on role - you design and you build. The scope spans the full data and AI layer: how data flows between systems, how it is shaped for AI consumption, how agents and services are architected to work together reliably at scale. You'll work in close partnership with the Principal Data Engineer, jointly shaping the architecture and evolution of the Data & AI domain. You'll be expected to independently make and own technical decisions, drive initiatives from design through production, and provide technical leadership across the team. You'll work across teams and contribute to shaping how we approach Data Fusion: bringing together signals from heterogeneous systems and turning them into actionable insights through AI and data engineering. This requires someone who can hold the big picture in their head while still caring deeply about the details of implementation. Beyond architecture, you'll own the technical execution of initiatives within the Data & AI domain - driving work from design through production, making trade-off decisions, coordinating with adjacent teams, and staying accountable for systems after they go live. We write code with AI - tools like Claude Code and Cursor are a core part of how we work at every level, including this one. At Technical Lead level we expect not just fluency but deliberate, opinionated use: knowing when to lean on AI, when to steer it hard, and when to step in entirely. This is a non-negotiable part of how we operate. What You'll Do Co-own technical architecture and system design with the Principal Data Engineer - covering data pipelines, AI flows, agent systems, and service integration patterns Lead design of data and AI flows across heterogeneous systems - defining how data is ingested, transformed, stored, retrieved, and consumed by agents and services Make and document architectural decisions independently when needed, providing clear reasoning and trade-off analysis Design and build MCP tools, RAG pipelines, and agent-facing APIs that connect AI systems to the data layer reliably Develop backend services with FastAPI as part of an event-driven architecture - hands-on, not just advisory Set and uphold engineering standards across the team: code quality, design patterns, review culture, and documentation practices Mentor engineers across the team - particularly on system design, data modelling, and AI integration patterns Use AI-assisted coding tools deliberately and help shape how the team uses them effectively Own the evolution of the Data & AI domain architecture, identifying technical debt, improving system design, and ensuring the long-term scalability and reliability of the platform Lead technical execution of initiatives from discovery to production - defining technical plans, driving implementation, overseeing rollout, and remaining accountable for post-release outcomes Act as the technical point of contact for initiatives within the domain, coordinating with Product Managers, engineers, QA, and adjacent teams to ensure successful delivery Collaborate closely with other Technical Leads and Principal Engineers to define shared interfaces, integration patterns, and cross-domain architectural decisions Drive engineering excellence in production through observability, monitoring, testing strategies, and operational readiness Participate in technical hiring and help shape the growth and technical direction of the Data & AI team What We’re Looking For Strong Python engineering background - production-grade code across data pipelines, backend services, and AI integrations; you write things that last and that others can extend Data architecture experience - proven ability to design systems that handle data at scale: schema design, storage strategy, pipeline architecture, and data modelling for both analytical and AI workloads AI systems design - solid understanding of how LLMs, agents, and retrieval systems fit together; experience designing or building RAG pipelines, multi-agent systems, or tool-augmented LLM workflows Backend and API development - strong experience with FastAPI or equivalent; comfortable designing service contracts and integration patterns across systems Event-driven architecture - hands-on experience designing and operating event-driven systems in production (Kafka, RabbitMQ, or similar) Docker and containerisation - confident at