Principal AI-Native System Enigneer

Principal AI-Native Systems Engineer

Location: UK Wide offices - include
- London, Manachester, Bristol, Ipswich or Birmingham

Job Location: G  Bristol
- Assembly, G  Ipswich
- Adastral Hub, G
-Birmingham-Three Snowhill, G
-London-BTHQ One Braham, G
-Manchester-New Bailey

Advertised Salary: Competitive with great benefits

Career Grade: CLC

Job Function: Data & AI

The Principal AI-Native Systems Engineer is a senior technical leadership role within DD Ops, accountable for designing and engineering complex cloud-native, data-intensive and AI-enabled systems that support network operations outcomes across RAN, Core, data and automation domains.

This role matters because BT is moving from large, coordination-heavy delivery models towards small expert engineering pods that use AI agents as force multipliers. The Principal AI-Native Systems Engineer owns the system engineering discipline, translates business problems into robust technical designs, and ensures that AI-assisted delivery remains governed, secure, testable and outcome-focused.

The role is hands‑on and accountable for technical outcomes from concept to production. It works directly with users, architects, product owners, software engineers, test engineers and technical business analysts to ensure the right solution is specified, built, validated and operated.

• Own system architecture:
  You will define the end‑to‑end architecture for AI‑native, cloud‑native and data‑intensive systems, including system boundaries, interfaces, data contracts, resilience patterns and operational controls.
• Lead specification‑first engineering:
  You will work directly with users and stakeholders to turn business problems into deterministic technical specifications, acceptance criteria and non‑functional requirements.
• Direct AI‑native delivery:
  You will use and orchestrate AI agents to accelerate design, coding, testing, documentation, infrastructure and deployment activities while retaining human accountability for correctness and quality.
• Set engineering standards:
  You will define reusable engineering patterns, guardrails, templates, prompts, review criteria and governance practices for AI‑assisted software delivery.
• Design distributed systems:
  You will design scalable, secure and resilient systems across cloud platforms, APIs, event‑driven architectures, data pipelines and observability patterns.
• Assure quality and production readiness:
  You will partner with AI‑Native Test Engineers to ensure generated and human‑authored outputs meet functional, security, performance, resilience and operational acceptance criteria.
• Influence and communicate:
  You will translate complex technical concepts into clear language for senior stakeholders, engineers and business users.
• Coach and develop capability:
  You will coach engineers in systems thinking, AI‑native engineering practices, software fundamentals and accountable technical decision‑making.
• Drive continuous improvement:
  You will convert delivery learning, incident feedback, cost insights and production signals into improved specifications, agent workflows and reusable delivery accelerators.

• Systems engineering depth:
  Extensive experience designing complex software systems, distributed systems, data platforms or cloud‑native services.
• AI‑native engineering mindset:
  Practical experience using AI‑assisted engineering tools or coding agents to improve software delivery, testing, documentation or design productivity.
• Technical fundamentals:
  Strong knowledge of algorithms, data structures, concurrency, operating systems, networking, APIs, integration patterns and performance trade‑offs.
• Cloud and platform experience:
  Good knowledge of cloud compute platforms, preferably AWS,…