Principal Engineer AI & Platform Strategy

With a particular focus on AI you will lead So Energys approach to designing building and operating AI-enabled systems across the business. This includes AI implementation in customer operations and contact centres automation and decision support internal tooling and platform capabilities that enable teams to ship faster with higher quality.

This role is not a big architect role in isolation. You will work across Engineering Product Data and Operations to create alignment establish standards and drive adoption ensuring So Energy becomes an AI-native organisation where teams can use AI safely effectively and confidently.

This is also a highly hands-on role. You are expected to stay close to the code and close to delivery personally leading and delivering high-impact initiatives that materially improve customer outcomes reduce operational complexity and shift key business metrics. You will be accountable not just for technical direction but for ensuring the work lands and moves the needle.

Your Impact

In this high-impact leadership role you will shape the technical direction of So Energy ensuring the organisation makes sound consistent technology decisions that deliver commercial value improve customer experience and reduce cost-to-serve.

You will:

• Define and drive company-wide technical strategy and architectural direction ensuring technology choices align to business outcomes risk posture and long-term scalability.

• Establish scalable platform patterns engineering standards and technical guardrails that enable teams to move fast without sacrificing reliability security or quality.

• Lead AI adoption as a strategic capability across the business driving practical implementation clear standards and measurable outcomes.

• Increase AI literacy across Engineering Product Operations and leadership enabling teams to adopt AI safely and effectively not just experiment.

• Personally lead and deliver So Energys highest-impact platform and AI initiatives ensuring solutions are production-grade adopted and materially improve key business metrics.
  

• Acting as So Energys technical strategy authority shaping platform investment priorities build vs buy decisions and technical standards across the business.

• Leading AI as a strategic capability defining how we design build and scale AI solutions across customer operations automation and engineering productivity.

• Establishing So Energys approach to agentic AI including patterns guardrails and production standards (evals observability security privacy cost controls and fail-safes).

• Driving AI literacy and adoption across Engineering Product and Operations through enablement playbooks and hands-on guidance.

• Working closely with the Head of Data to build scalable data platform foundations that enable AI automation and high-quality decision-making.

• Mentoring senior engineers and technical leaders raising the bar for engineering quality delivery and technical decision-making.

• Taking personal accountability for delivering high-impact initiatives end-to-end staying hands-on when needed to ensure work lands and materially improves business outcomes.
  

• Demonstrable experience setting technical direction across multiple teams balancing autonomy with strong standards and guardrails.

• Deep system design and architecture capability including designing scalable resilient secure distributed systems.

• Strong hands-on engineering fundamentals including recent experience writing reviewing and reasoning about production code.

• Strong stakeholder influence: able to challenge constructively align senior stakeholders and create clarity in ambiguity.

• Strong leadership experience mentoring senior engineers and raising the technical bar across the organisation.
  

AI Agentic Systems & AI-Native Engineering (Essential)

• Strong experience building and deploying production AI systems including LLM-enabled applications and automation.

• Practical experience with agentic AI systems (tool use orchestration multi-step workflows decision loops human-in-the-loop patterns).

• Experience with AI frameworks and orchestration tooling such as:

• LangChain LlamaIndex CrewAI or equivalent

• Strong working knowledge of modern ML/LLM platforms on at least one major cloud:

• AWS (e.g. Bedrock SageMaker event-driven architecture) and/or

• GCP (e.g. Vertex AI BigQuery ML cloud-native data ML pipelines)

• Strong understanding of what good looks like for production AI:

• evaluation strategies and regression testing (AI evals)

• prompt/version control and release management

• observability and monitoring for AI systems

• cost controls latency trade-offs model selection

• privacy security compliance-by-design and auditability

• Strong practical use of AI-native coding workflows and tools such as Claude Code Cursor Gemini Code Assist Codex or equivalent with the ability to embed these ways of working into engineering culture.

Desirable

• Experience with contact-centre platforms ideally Amazon Connect and/or AI-enabled customer operations tooling.

• Experience in highly regulated industries (energy fintech utilities telecoms).

• Familiarity with platform engineering CI/CD infrastructure automation and developer experience golden paths.