AI Solutions Engineer

Description Enterprise Integration Platform is a global function within the Chief Technology Office, comprising approximately 425 staff members located worldwide. We are tasked with defining and executing strategies for several critical products across the organisation, ensuring their availability, recoverability, and security. We are accountable for and support numerous Important Business Services within the organisation. This role is for an AI Solutions Engineer responsible for uncovering, shaping, and delivering AI opportunities across the platform by working directly with product teams. You’ll use data, operational insights and research techniques to identify high-value problems, validate feasibility through rapid prototypes, and then engineer production-ready solutions that improve customer outcomes, operational efficiency, resilience, and/or control. You’ll partner closely with an AI Product Manager to refine demand, prioritise the opportunity pipeline, and translate ideas into a clear delivery plan. Unlike pure research or “innovation lab” role, success here is measured by what reaches production: secure-by-design, observable, supportable, and adopted. Role expectation  Partner with platform product teams to identify and qualify AI opportunities using a mix of data analysis, user pain points, process mining/telemetry, and operational insights.  Turn opportunities into well-defined use cases (problem statement, target users, success measures, constraints, risks/controls) and support the AI Product Manager with sizing and prioritisation inputs.  Rapidly prototype and validate solutions (PoCs/spikes) to prove technical feasibility and value, then harden them into production-grade services or features.  Engineer end-to-end implementations into production, including integration with existing platform services (APIs, data sources, identity/access, audit, logging/monitoring).  Apply a “measure everything” mindset: define KPIs with product teams, instrument solutions, and use evidence to iterate, optimise, or stop work quickly when needed.  Contribute reusable assets to accelerate adoption (templates, reference implementations, shared libraries, runbooks, and engineering standards).  Communicate progress, risks, and dependencies clearly, keeping delivery moving at pace across multiple workstreams. Skills Required Essential  Strong hands-on software engineering experience delivering production services (design, build, test, deploy, operate).  Strong analytical skills with experience using data to identify opportunities and measure outcomes (e.g., logs/telemetry, operational metrics, product analytics, SQL/Python).  Strong scripting/programming skills (Python preferred; Go/Bash/Java also useful depending on stack).  Experience taking prototypes into production, including non-functional requirements (security, resilience, performance, observability, supportability).  Ability to work effectively with product teams to translate ambiguous problems into deliverable engineering work.  Working experience in Agile methodologies.  Strong documentation and collaboration mindset.  Fluency in written and spoken English and comfortable working in a multi-cultured/global environment. Desirable  Experience delivering AI/ML or GenAI solutions (e.g., model integration, RAG patterns, evaluation approaches, prompt/tooling patterns).  Familiarity with Responsible AI / governance expectations (privacy, bias, auditability, model risk, technology controls), especially in regulated environments.  Experience with engineering practices (containers/Kubernetes, CI/CD, IaC, secrets management, API gateways).  Experience building reusable “paved road” enablement for other teams (golden paths, templates, internal developer tooling).