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AI Engineering Lead
AI Engineering Lead
(Leicester or London, Hybrid)
Bellrock is seeking an experienced AI Engineering Lead to own and architect its internal AI systems—bringing AI ideas from concept to production while guiding a team of AI Graduates. This is a hands-on leadership role focused on vision, technical excellence, safety, scalability, and mentorship.
Location & Flexibility
- Based in either Leicester or London, with fully hybrid (home/office) working arrangements
About the Role
You will be the most senior technical lead within Bellrock’s AI team, shaping core systems that power automation, workflows, and data-driven operations. Your responsibilities include:
- Technical ownership: Design and operationalise AI systems (agentic models, pipelines, integrations) across the business.
- End-to-end delivery: Steer use cases from prototype to production with security, reliability, and maintainability.
- Strategic decision-making: Define standards around tooling, prompt engineering, model access, and security boundaries.
- Collaboration: Work closely with the Head of AI and Delivery Manager to translate business goals into technical roadmaps.
- Governance & risk: Support compliance, data residency, and safeguards (e.g. least-privilege access, kill-switches).
- Team development: Mentor AI Graduate Analysts, expanding their technical rigour and hands-on capabilities.
- Learning & innovation: Stay ahead of AI advancements, evaluating tools and frameworks for Bellrock’s needs.
This role demands autonomy, pragmatism, and broad ownership, while fostering collaboration between technical and non-technical stakeholders.
Key Responsibilities
Technical Architecture & Delivery
- Architect AI workflows (e.g. agentic systems, automation pipelines) and align with internal data/data pipelines.
- Lead the build-out of production-grade AI systems with a focus on scalability, security, and traceability.
- Embed engineering standards: data hygiene, prompt design, tool-use boundaries, and robust API integrations.
- Evaluate foundation models, orchestration layers, and frameworks (e.g. LangChain, LlamaIndex) with attention to cost/performance.
- Collaborate with the AI Delivery Manager to break use cases into technical milestones and roll-out plans.
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Governance & Safety
- Advise on AI risk assessment, including data residency, access control, and safegaurds (e.g. kill switches, reversibility).
- Ensure AI systems adhere to Bellrock’s governance policies and regulatory requirements.
Leadership
- Mentor young talent: Train AI Graduate Analysts to develop technical expertise, critical thinking, and scalable engineering practices.
- Build high-value solutions: Ensure products deliver defendable outcomes—cohesive, well-documented, and aligned with growth.
AI-Centric Mindset
- Stay agile and curious: Actively prototype, experiment, and apply AI in work. Broaden perspective through problem-solving and self-improvement.
- Drive scaling Wright’s philosophy: Work autonomously yet collaboratively, taking ownership on tough decisions.
Requirements
Experience
- Proven track record in building AI applications, e.g. chat agents, workflow automators or data tools.
- Experience with foundation models in production environments (e.g. Anthropic Claude, OpenAI, Azure AI, AWS Bedrock).
- Hands-on with LangChain, LlamaIndex, or equivalent orchestration frameworks to build agentic workflows.
- Strong coding skills in Python or JavaScript/TypeScript.
- Stakeholder management: Ability to translate complex technical requirements and trade-offs for non-technical audiences.
Technical Expertise
✚ Prompt engineering and RAG (Retrieval-Augmented Generation) ✚ API design and microservices integration ✚ Data governance and compliance (e.g. access controls, auditability, data residency) ✚ Familiarity with tool-use patterns (e.g. MCP or similar frameworks, though not required). ✚ Security-first mindset in AI — understanding model drift, adversarial testing, and safety patterns.
Soft Skills
- Pragmatic leadership: Balances innovation and production constraints with a focus on feature safety and scalability.
- Mentorship: Cultures a team’s growth through code reviews, project discussions, and skill-building workshops.
- Confidence in ambiguity: Thrive in evolving fields by solving hard problems without micromanagement.
- Relatability: Communicates technical concepts clearly to engineers and product teams.
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Nice-to-Haves
- Experience scaling AI systems across teams and organisational data silos.
- Feedback on engineering practices from a supervisor or peer review programme.
- Prior history in mentoring new grads (e.g. via structured programmes or 1:1 support).
Benefits
Bellrock prioritises employee well-being, growth, and work-life balance. As an AI Engineering Lead, you’ll access:
- Handy holiday — 25 days annual leave, all bank holidays, plus 1 thank-you day.
- Pensions, life cover, and insurance (e.g. health cashplan, virtual GP).
- Workplace equality benefits:
- Enhanced parental leave (maternity/paternity/adoption).
- Holiday Purchase Scheme: Buy 5 additional days of paid leave per year.
- Wellness programs: Health Assured support and counselling services.
- Workplace perks:
- Cycle-to-work car scheme, salon saver, discount programmes, liftshare matching and better remote setup costs.
- People culture: Bellrock invests in ambitious careers through mentorship, training, and a supportive network.
- Innovative workplace: Creative autonomy to turn ideas into AI realities with confidence.
Why Bellrock?
At Bellrock, the people are the driving force. Our dedication lies in helping you grow—from fostering meaningful careers to innovation. It’s about your opportunities as much as our own. Whether you seek fresh challenges or a long-term professional direction, we’ll craft a path with you at its core.
We’re committed to an equitable workload. If this role is a good fit through your qualifications or untraditional path, we want to hear from you.
Apply in your own way—tell us who you are rather than meeting an ideal template.
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