Ai Engineer

Sr2 Rec Ltd; England; Hybrid; GBP 96,000 - 165,000; Full time

Job summary

SR2 Consulting is recruiting Senior AI Engineers to join a financial-services organisation in London. You will build production-quality AI applications, integrating with enterprise data and APIs, while ensuring security, auditability and cost controls.

The role is hands-on, offering influence over engineering practices and technology choices, with a London hybrid setup (2–3 days onsite) and Inside IR35 contract terms.

Qualifications

• Strong Python engineering skills and tested API development.
• Production experience with AI or ML applications.
• Hands-on LLM integration, retrieval and embeddings.
• Experience in financial services or regulated industry is essential.
• Understand data sensitivity, auditability and access controls.

Responsibilities

• Collaborate with business teams to identify AI value.
• Build production-quality AI applications with retrieval-augmented generation.
• Connect apps to enterprise data and APIs with proper permissions.
• Develop evaluation methods for accuracy, security and cost.
• Implement logging, fallback, and human review in workflows.
• Work with platform/DevOps to deploy and monitor applications.
• Contribute reusable components and documentation.

Skills

Python

LLM integration

SQL

APIs

DevOps

Distributed systems

Education

Experience in regulated industries

Tools

FastAPI

Git

Docker

Snowflake

MLflow

LangGraph / Semantic Kernel

Job description

Senior AI Engineer | Financial Services | Contract

Three opportunities | London hybrid, 2-3 days onsite | Inside IR35

Building an impressive demo is one thing. Making AI dependable enough for people to use in a complex financial-services environment takes a different level of engineering.

SR2 Consulting is looking for three Senior AI Engineers to join a financial-services organisation developing its internal AI capability. You'll work alongside business stakeholders, architects and platform specialists to turn promising use cases into secure, measurable and supportable applications.

This is a hands-on role with scope to influence engineering practices, technology choices and how AI becomes part of everyday business workflows.

What you'll be doing

• Work with business teams to understand processes, challenge assumptions and identify where AI can deliver practical value.

• Build production-quality AI applications, including retrieval-augmented generation, tool-enabled assistants and agentic workflows where appropriate.

• Connect applications to enterprise data, APIs and existing systems, respecting access permissions and information boundaries.

• Develop evaluation approaches covering accuracy, reliability, security, latency and cost.

• Build appropriate human review, exception handling, logging and fallback behaviour into AI workflows.

• Work with platform and DevOps engineers to deploy, monitor and improve applications.

• Contribute reusable components, code reviews, documentation and knowledge transfer as the internal team grows.

What we need

• Strong Python engineering skills, with experience building tested, maintainable applications and APIs.

• Evidence of taking AI or machine-learning applications into production and supporting them beyond launch.

• Hands-on experience with LLM integration, retrieval, embeddings and structured outputs.

• Experience delivering in a regulated industry is essential, ideally banking, insurance, investment management or wider financial services.

• An understanding of how sensitive data, auditability, access controls and operational resilience affect engineering decisions.

• Confidence working directly with business stakeholders and explaining technical trade-offs.

• Strong SQL and experience integrating with enterprise data platforms.

Relevant technology experience

Python, SQL, API frameworks such as FastAPI, Git, Docker and automated testing are particularly useful. Experience with Snowflake is highly relevant.

We welcome experience with services such as Amazon Bedrock, Azure OpenAI or Azure AI services, and models from providers including Anthropic, OpenAI and open-source ecosystems. Frameworks such as LangGraph or Semantic Kernel, vector search and evaluation tools such as MLflow or LangSmith would also be useful.

You do not need every tool listed. We are looking for sound engineering judgement and the ability to choose an appropriate approach, rather than allegiance to one model or framework.

Contract details

London hybrid, with 2-3 days onsite. Inside IR35. Appointment is subject to the required security screening and clearance process.