Senior AI Engineer

Overview

In this role you will lead the delivery of enterprise AI capabilities, designing and building agentic applications and platform services that scale across the firm. You will set implementation patterns, review peers, and own production systems from conception to live operation, including governance and observability. You will work with Percepta engineers to ensure platforms are maintainable and extensible, while driving end-to-end business-area applications and SaaS decommissioning to consolidate in-house capabilities. This is a hands-on, senior IC role shaping the AI Engineering practice as the team forms.

Pay / Benefits

• Hybrid working
• Generous holiday policies
• Health and wellbeing benefits
• Paid volunteer time
• Professional development support
• Family/maternity/paternity leave

Responsibilities

• Build and run AI products and platform, end-to-end ownership through live operation
• Design reusable components, libraries, skills, and connectors for enterprise use
• Implement infrastructure as code, manage CI/CD, and ensure clear ownership and controls
• Investigate incidents, drive recovery, and fix root causes in production services
• Engineer agentic applications and workflows, including prompt/context engineering and tool use
• Develop model routing, orchestration, and safe execution with enterprise-grade controls
• Create AI-ready data views, connectors, and governance for Snowflake and enterprise platforms
• Extend Accio to expose new datasets via a governed interface
• Lead end-to-end business-area apps on the AI stack and drive SaaS decommissioning
• Establish evaluation, controls, and release evidence as part of AI governance
• Mentor engineers, contribute to engineering standards, and collaborate with AI Architecture and Percepta
• Work with procurement and finance to consolidate licenses and ownership of built solutions

Key requirements

• At least six years of software, data, or platform engineering experience
• Production experience with LLM applications and agentic systems
• Strong Python and SQL
• Hands-on experience building MCP servers, tools, skills, or connectors
• Experience with Azure cloud including containers/serverless, IaC, CI/CD, identity, RBAC, secret management
• Experience owning production services, monitoring, incidents, upgrades, and lifecycle management
• Good judgement in regulated environments translating security, privacy, risk, and audit requirements into technical controls
• Experience mentoring engineers and leading technical work without direct reporting authority
• Clear communication with engineers, control functions, and business stakeholders

• Mentoring and enabling others
• Strong communication with technical and business teams
• Judgement in regulated environments
• Python
• SQL
• LLM applications and agent frameworks

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