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Global S&C_ATIOS_Strategy Consultant

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: WeAreTechWomen
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    AI Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 GBP Yearly GBP 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Job Role:

Strategy Consultant - Global S&C ATIOS

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 services.

Quant

AI 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.

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.
Qualification Must‑have
  • Bachelor's degree in computer science, engineering, mathematics, physics, economics, or a related field. An associate degree is acceptable with at least 2 additional years of directly relevant experience and clear evidence of shipped engineering work.
  • Minimum 3 years of experience in consulting or other client‑facing technical delivery roles, with evidence that you have helped move products, internal tools, or workflow systems beyond proof‑of‑concept stage.
  • Minimum 3 years of hands‑on experience in one or more of the following areas: backend services, APIs and integrations, full‑stack delivery, data pipelines, model‑serving or machine learning workflows, or agentic orchestration systems.
  • Strong coding ability in Python plus one complementary engineering surface such as Type Script or JavaScript, front‑end delivery, cloud or platform engineering, or infrastructure automation.
  • Sound engineering judgment around enterprise hardening and evaluation, including experience with several of the following: authentication, role‑based access control (RBAC), observability, security, release discipline, regression testing, or experiment frameworks for AI, machine learning, or agentic workflows.
Nice‑to‑have
  • Experience with tool‑using systems, retrieval, evaluation pipelines, agent orchestration, or MCP‑style integrations.
  • Experience building expert‑facing interfaces, workflow products, or technical demos that had to stand up in front of real users.
  • Experience packaging desktop applications or supporting Windows‑heavy enterprise environments.
  • Exposure to forecasting, anomaly detection,…
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