Lead AI Engineer

Newcastle upon Tyne, United Kingdom | Posted on 17/07/2026

Scrumconnect Consulting is a multi-award-winning digital consultancy, recognised for delivering impactful and innovative technology solutions across UK government departments.

Our work has positively influenced the lives of over 40 million UK citizens.

We are passionate about user‑centred design, agile delivery, and building digital services that make a real difference — and we’re now scaling that expertise into large, high‑stakes AI adoption programmes across the public sector.

Overview

We’re looking for a Lead AI Engineer to be the hands‑on technical builder at the core of a large‑scale AI Operating Model programme for a central government department.

Where the Lead Technical Architect sets direction, you turn it into production‑grade systems — semantic search, RAG pipelines, and broader generative AI capability — integrated into complex legacy and multi‑cloud environments handling high‑volume, sensitive public sector data.

You’ll work inside a collaborative "Rainbow Team" alongside civil servants and the wider delivery team, staying close to the code while also mentoring engineers and helping build the internal capability the department needs to eventually run these systems without long‑term reliance on external suppliers.

Key Responsibilities

• Design, build, and ship production AI components — RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers — writing high‑quality, tested, maintainable code and staying close to implementation rather than delegating it away.
• Lead the engineering practice within your delivery team: set coding standards, review designs and pull requests, unblock technically complex problems, and mentor other engineers day to day.
• Implement guardrails the Architect designs — bias mitigation checks, evaluation harnesses, human‑in‑the‑loop review points — so that Responsible AI principles (ATRS alignment, NCSC "Secure by Design", meaningful human control) are enforced in the running system.
• Build AI services to be secure‑by‑default and observable in production: logging, monitoring, alerting, and rollback paths appropriate for sensitive public‑sector data and high‑availability requirements.
• Work within the OKUA (Ownership, Knowledge, Understanding, Awareness) framework and "Docs‑as‑Code" practices to pair with and upskill internal government engineers, ensuring capability genuinely transfers rather than staying locked in the consultancy team.
• Favor low‑modality, resource‑efficient designs where they meet the need — right‑sizing models and infrastructure rather than defaulting to the largest or most expensive option — in line with the programme’s Green AI and Net Zero commitments.
• Required Skills & Experience
• Engineering level: Lead Engineer mapped to the Government Digital and Data (DDa T) framework.
• Coding and Scripting (Expert) — writing production‑grade, well‑tested code; setting standards for others; comfortable owning components end‑to‑end.
• Systems Design (Practitioner) — designing components that integrate cleanly into a wider, architect‑defined system; understanding trade‑offs across the stack.
• Data Engineering (Practitioner) — building reliable pipelines to ingest, clean, and prepare data (including unstructured/legacy sources) for AI consumption.
• Dev Ops / Continuous Delivery (Practitioner) — CI/CD pipelines, infrastructure‑as‑code, and automated deployment for AI workloads specifically.
• Testing & Evaluation (Practitioner) — beyond conventional unit/integration testing, building evaluation harnesses for AI system quality: retrieval accuracy, hallucination rate, bias/fairness checks.
• Problem Solving (Practitioner) — diagnosing and resolving complex, ambiguous technical issues under production pressure.
• Agile Working (Practitioner) — delivering iteratively within a blended, multidisciplinary team including civil servants.
• Strong general‑purpose programming (most commonly Python) applied to AI/ML systems.
• Semantic search, vector/embedding infrastructure, and RAG pipeline construction.
• LLM orchestration and agentic frameworks (e. g., Lang Chain/Llama Index‑style tooling, multi‑agent patterns).
• Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing).
• LLMOps/MLOps — model versioning, deployment, monitoring, and rollback for AI services in production.
• Cloud‑native engineering across major providers (AWS, Azure, or GCP), including their AI/ML tooling.
• Containerisation and infrastructure‑as‑code for repeatable, auditable deployments.
• Secure‑by‑design engineering appropriate to sensitive public‑sector data.
• AWS / Azure / GCP certifications (associate or professional level).
• Prior delivery of AI or digital services within UK central government or wider public sector.
• Experience fine‑tuning or adapting open‑source/foundation models for a specific domain.
• Open‑source contributions or active engagement in AI/ML engineering communities.
• Experience designing for sustainability/Green IT commitments.
• Location and Working Pattern

Hybrid, based from Newcastle upon Tyne, with on‑site attendance required for workshops, knowledge‑transfer sessions, and onboarding.

All production system and data access must be performed solely from within the UK.

As a Disability Confident Level 1 employer, we provide reasonable adjustments throughout recruitment and employment to ensure equal opportunity for all.

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