Description
Senior & Principal AI Delivery Consultants – Capital Markets Outside IR35 and Hybrid Working Location: London Start date: ASAP Contract requirement: 2–4 consultants, with the strongest two candidates prioritised for initial presentation.
We are supporting a Tier-1 global financial institution looking to bring in experienced AI consultants who have successfully delivered commercial AI solutions into live production environments.
The bank has several AI initiatives underway but needs additional engineering capacity to move projects beyond experimentation and into production.
Previous permanent hiring efforts have not filled the requirement, so the priority is to identify high-quality consultants who can start quickly and deliver from day one.
These are hands-on delivery roles, not research, advisory or proof-of-concept positions.
Consultants will be responsible for designing and building AI solutions, integrating them into the bank’s existing technology environment, and navigating the governance and approval processes required for production deployment.
Initial project: AI-driven program trading The initial initiative focuses on using AI to support trading decisions by combining historical client behaviour with predicted market movements to generate actionable recommendations for trading desks.
The solution will involve: Modelling client behaviour and historical trading activity. Analysing and incorporating market signals and predictions. Developing a recommendation layer that supports real trading decisions. Delivering within a Tier-1 regulated banking environment.
Further projects are expected across the wider AI programme, including foreign exchange (FX) and digital sales.
Candidates should therefore be suitable for a pipeline of AI delivery initiatives rather than a single project.
Core technical requirements
- Strong Python development skills, including production-quality code.
- Hands-on experience with machine learning and real-world model development.
- Practical experience with LLMs, agentic frameworks, orchestration and AI evaluation.
Wider technology context
The bank operates a large, predominantly Java/Spring Boot microservices estate, with some Python, distributed across multiple data centres.
AI solutions must integrate with the existing architecture and internal orchestration platform rather than replace it.
AI-assisted development tools, including Windsurf, Claude and Devin, are part of the engineering workflow.
A key challenge is getting AI solutions through model-risk validation, governance and production approval.
Candidates who have successfully navigated comparable enterprise approval processes will be particularly valuable.
Role 1: Principal Consultant – AI Delivery
Headcount: 1, with potential for a second Principal depending on demand.
Role purpose Lead the technical design and delivery of AI solutions, working directly with business stakeholders to shape requirements, make architectural decisions, write production code and take solutions through model-risk and production governance.
This is a senior, hands-on role combining technical leadership, engineering delivery and stakeholder engagement.
Essential experience
- Commercial AI delivery: 10+ years of commercial engineering or data science experience, including AI/ML systems successfully deployed into production.
- Candidates must be able to explain the system, its users and the approval process it went through.
- Production governance: Proven experience taking AI solutions through enterprise governance, including model risk, validation, explainability, monitoring, audit trails and controls. This is the most important differentiator.
- Python and machine learning: Strong Python skills and practical expertise across feature engineering, model training, evaluation, drift detection and monitoring.
- Modern AI development: Hands-on experience with LLMs, agentic frameworks, RAG, orchestration and evaluation frameworks, alongside using AI tools to accelerate their own engineering work.
- Solution design: Ability to turn loosely defined business requirements into a clearly scoped, technically viable solution.
- Technical leadership: Confidence working directly with senior stakeholders, business sponsors and engineering teams, acting as the primary technical contact for the client.
Desirable experience
- Capital markets, trading, execution, program/algorithmic trading or FX.
- Recommendation or decision-support systems using client behavioural data.
- Experience delivering AI within a Tier-1 regulated bank.
- MLOps, containerisation, CI/CD, model serving and observability.
- Integrating solutions into existing enterprise orchestration platforms.
Role 2: Senior Consultant – AI Engineer
Headcount: 1–3.
Role purpose Build and deploy AI solutions in line with the programme’s priorities, working under the Principal Consultant’s direction.
Responsibilities include developing data pipelines, implementing and evaluating models, building agentic workflows and producing the technical evidence required for production approval.
Candidates must be hands-on, delivery-focused and able to contribute productively from day one.
Essential experience
- Commercial AI delivery: 5+ years of commercial engineering experience, including hands-on delivery of AI/ML solutions into production.
- Python engineering: Strong Python skills in production codebases, beyond notebooks and experimentation.
- Practical machine learning: Experience building, evaluating and deploying models using real business data.
- AI tooling: Familiarity with current LLM and agentic frameworks, as well as AI-assisted development tools such as Windsurf, Claude, Devin or equivalent.
- Production readiness: Understanding of AI testing, evaluation, monitoring and documentation requirements, with the ability to produce this evidence as part of the build.
- Delivery mindset: Comfortable working within an established client delivery process, following priorities and delivering at pace.
Desirable experience
- Financial services, banking, trading or capital markets data.
- Time-series, behavioural or market-data modelling.
- Data engineering, including pipelines, feature stores and streaming.
- Cloud platforms and MLOps tooling.
- Java experience to support integration with the existing technology estate.
What Good Looks Like
The ideal candidates are experienced AI engineers who have moved beyond experimentation and can demonstrate tangible production outcomes.
For the Principal Consultant, the priority is someone who can lead the technical solution, engage business stakeholders and demonstrate a proven track record of getting AI through enterprise model-risk and governance approval.
For the Senior Consultant, the priority is someone who can build, test and deploy AI solutions in production, using strong Python and modern AI tooling while ensuring that testing, evaluation, monitoring and documentation are built into the delivery process.
The most important screening question for both roles is: Can the candidate describe a commercial AI solution they personally helped deliver into production, what they contributed, and how the solution passed the necessary validation and approval gates?