Principal Engineer - Platform Enablement

Centrica, Technology is a core driver of how we deliver our strategy. You’ll join a team modernising our platforms, strengthening cyber and operational resilience, and advancing a product‑led way of working that brings engineers, data specialists and business experts together to deliver meaningful outcomes at pace. We’re scaling automation and AI from proof‑of‑concept into real, end‑to‑end change - improving customer journeys, reducing cost‑to‑serve, accelerating delivery, and building the digital foundations that underpin everything from energy trading and risk to field operations and critical infrastructure. If you want to work on complex, high‑impact problems using modern engineering practices, and help build reusable platforms that will shape how Centrica operates over the next decade, this is the place to do it.

An opportunity to play your part:

• The Principal Software Engineer provides the technical leadership, architectural vision, and engineering standards required to evolve and scale the Field Platform.
• The role ensures that our platform delivers a unified, performant, secure and resilient experience that enables thousands of field colleagues to work efficiently, safely and effectively every day.
• The role is expected to use automation, data and AI‑enabled tooling to reduce repetitive work, improve code quality, speed up development cycles and strengthen reliability—while retaining full human accountability for technical judgement and decisions.

Day to day:

• Define & evolve the Field Platform architecture: Set the long‑term architecture, patterns, and guardrails for Field platform services to ensure scalability, resilience, interoperability, and a unified experience.
• Drive consolidation and simplification of the estate: Lead the rationalisation of the platform into a coherent platform, reducing duplication, technical debt, maintenance costs, and operational complexity.
• Shape cross‑domain technical design decisions: Partner across Product, Architecture, Supply Chain, Scheduling, and Field Operations to drive consistent data models, integration patterns, UX principles, and standards across all field workflows.
• Identify and deliver new digital capabilities: Work with product and business leaders to define new capabilities (such as supply chain, quoting, workflow optimisation, knowledge management) to enhance safety, compliance, customer experience, and productivity.
• Establish engineering excellence across teams: Champion high engineering standards including clean architecture, CI/CD automation, observability, testing strategies, release processes, telemetry, performance tuning, and secure‑by‑design principles.
• Lead platform performance, reliability & offline capability: Ensure the environment performs reliably in challenging field conditions (such as poor signal or offline mode), with focus on failover behaviours, caching, performance profiling, and user trust.
• Influence and steward Security, SRE, Quality and Platform‑wide capabilities: Shape quality, resilience, and security strategies across teams—ensuring teams adopt shift‑left testing, strong security hygiene, consistent observability, and reliable operational processes.
• Improve how work is done: Continuously identify opportunities to automate, simplify, reduce cycle time, improve developer experience, adopt new tools and AI, and scale better engineering practices across squads.

Key Stakeholders:

• The Principal Software Engineer works closely with the Head of Engineering to align on engineering strategy, technical priorities and delivery performance.
• They partner frequently with Product Managers to translate business needs into technical solutions and ensure roadmap clarity.
• Collaboration with Field Operations SMEs ensures platform enhancements meet operational, safety and compliance requirements.
• In addition, the role builds relationships with external partners and tooling providers (such as Microsoft and Datadog) through hackathons, roadmap discussions and innovation sessions to explore performance, monitoring and platform optimisation opportunities.

Leadership:

• Leadership Model (no direct line management): Lead through influence and expertise across squads, shaping backlog, standards and adoption; coach analysts/engineers; role model product‑led, iterative delivery and high bar for quality/controls.
• Membership & Forums: Participate in relevant governance/design forums.
• Capability Uplift: Build functional playbooks, patterns and guardrails; run knowledge shares and communities of practice.

What We Need From You:

• Nature of Thinking Required: Resolves complex, cross‑domain technical challenges involving mobile, backend APIs, orchestration layers, and field operational workflows. Balances near term delivery pressure against long term architectural sustainability. Solves ambiguous problems with incomplete data, designing scalable patterns that support multiple business domains.
• Decisions: Owned: Field platform architecture, coding standards, integration patterns, security baseline, technology choices, performance strategies. Acceptance of technical designs, readiness for release, critical code reviews.
• Decisions: Influenced: Product roadmap priorities, UX direction, cross team delivery sequencing, partner tool selection, funding for technical investments.
• Use of Insight, Data & Automation: Uses telemetry, profiling tools, error tracking, synthetic monitoring and AI‑assisted diagnostics to drive decisions. Validates but does not blindly trust automated or AI‑generated insights; human in the loop accountability remains primary.
• Constraints & Frameworks: Centrica architectural frameworks, security and data privacy standards, mobile platform patterns, operational governance.

Core Competencies & Technical Skills (AI and emerging technology):

• Designs, integrates and operates AI‑enabled solutions within enterprise environments, including prompt‑driven workflows, retrieval‑augmented systems and AI agents.
• Applies structured evaluation, testing and monitoring practices to ensure AI outputs are reliable, secure and compliant with organisational guardrails.
• Prepares and manages data used in AI workflows and takes responsibility for the responsible lifecycle of AI features from experimentation through deployment and continuous improvement.

Business Expertise:

• Understanding of field workforce operations (installation, service, repair).
• Awareness of compliance, safety, regulatory needs related to field processes.
• Experience working in product‑led organisations and cross functional teams.