AI Engineer - Global Strategy Consultant
On-site · London, England, United Kingdom
Job Summary
AI Engineer role focused on turning quantitative prototypes into enterprise-ready tools and workflows across cloud and on-prem environments. You’ll work on building reusable tools, services, and demo-to-pilot-to-scale assets, with emphasis on robust evaluation, governance, RBAC, authentication, observability, and deployment discipline. The role spans both conventional systems and agent-assisted architectures, requiring collaboration with quant leads and cross-surface ownership of data flows, model-serving surfaces, and demo hardening. Strong emphasis on delivering production-ready, enterprise-grade software with measurable model logic and governance.
Required Qualifications
- 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 TypeScript or JavaScript, front-end delivery, cloud or platform engineering, or infrastructure automation.
- Experience with authentication, 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 packaging desktop applications or supporting Windows-heavy enterprise environments.
- Exposure to forecasting, anomaly detection, optimization, time-series systems, or other decision-support workflows.
- Experience in energy, commodities, financial, trading, market operations, or industrial workflows.
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