AI Engineer - Global Strategy Consultant

Job Role: AI Engineer - Strategy Consultant

Location: London

Career Level: 9 Consultant

Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge.

We believe in inclusion and diversity and supporting the whole person. Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual, and Integrity. Year after year, Accenture is recognized worldwide not just for business performance but for inclusion and diversity too.

“Across the globe, one thing is universally true of the people of Accenture: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live. It is personal to all of us.” – Julie Sweet, Accenture CEO

QuantAI is building cutting-edge AI-native decision-system assets for energy, commodities, financial, trading, and industrial operations.

We are looking for engineers who can take strong quantitative and artificial intelligence (AI) work and turn it into enterprise-safe products: interfaces, packaged desktop applications, APIs, services, workflow systems, and demos that are credible enough for pilots and durable enough for scaled delivery.

Success here is not raw model novelty or polished demos in isolation. It is strong algorithms wrapped in workflow, governance, evaluation, and packaging. This role is engineer-first and shipping-first. The engineering covers two surfaces that both ship as product: conventional systems on one side, agent-assisted systems on the other.

The team is too small for either to be someone else's problem, and you should be able to operate across both -- though you will likely lead with strength in one.

What you'd work on

• Turn quantitative prototypes into reusable tools, services, packaged desktop applications, interfaces, and workflow products that can move from internal demo to client pilot to scaled offer.
• Ship across both cloud-hosted services and locally distributed desktop applications, including Electron-based apps when the workflow or client environment calls for it.
• Build enterprise hardening into the productization layer, including authentication, role-based access control (RBAC), observability, security, release quality, cost controls, and deployment discipline.
• Build evaluation, regression, and release discipline into the productization layer so model logic and agent behavior remain measurable as systems change.
• Work closely with the quant lead so model logic, evaluation intent, and governance requirements survive the move into production.
• Make pragmatic architecture choices across large language models (LLMs), deterministic rules, and hybrid systems based on value, latency, cost, and reliability.
• Help shape repeatable build patterns so strong prototypes become faster, more reliable, and more reusable over time.

Platforms and interfaces

• Own data flows, APIs, services, model-serving surfaces, front-end and desktop application surfaces, continuous integration and continuous delivery (CI/CD), and demo hardening.
• Build the systems that make quantitative work feel polished, reliable, and enterprise-ready for expert users and client stakeholders.

Agent-assisted systems

• Own the agentic harness layer — evaluation frameworks, reviewer loops, control-plane behavior, orchestration, and tool integration — that applications and MCPs wrap around.
• Design opinionated harnesses that expose through MCP or similar integration patterns without overfitting to one vendor or one moment in the tooling market.