Salary Range: £90,000 – £100,000 per annum
Role Type: Full‑Time, Permanent
Start date: As soon as possible
The Lead AI Engineer Role
As we continue our mission to be the market‑leading insurance platform for agile insurers, we’re excited to begin the search for a Lead AI Engineer to help shape the next generation of intelligent capabilities within the Send platform.
In this role, you will lead the design, development, and productionisation of AI‑powered services built on top of public large language models (LLMs), enabling insurers to unlock deeper insights, automate workflows, and enhance underwriting decisions. You will own the end‑to‑end lifecycle of AI features—from rapid prototyping through to resilient, observable, production‑grade systems—within a regulated financial services environment.
This is a hands‑on leadership role where you will set the technical direction for AI engineering at Send, mentor a growing team, and collaborate closely with data engineering, product, and compliance teams. Together, you will deliver AI capabilities that are scalable, secure, auditable, and deliver real commercial value to insurers using the Send platform.
What You’ll Be Doing as a Lead AI Engineer
Designing and delivering AI‑powered services
- Architect and build production‑grade services that integrate with public LLM APIs (such as OpenAI, Anthropic, Google, Cohere, or similar).
- Develop capabilities including prompt engineering, retrieval‑augmented generation (RAG), fine‑tuning pipelines, and agent‑based workflows.
- Design robust API layers, orchestration patterns, and evaluation frameworks to ensure reliable, cost‑efficient, and low‑latency AI features.
- Implement guardrails, content filtering, and output validation suitable for a regulated financial services environment.
Building and evolving the AI platform
- Define and evolve Send’s AI platform architecture, including embedding stores, vector databases, prompt versioning, and experiment tracking.
- Build containerised, cloud‑native services using modern infrastructure approaches (Docker, Kubernetes, serverless).
- Develop CI/CD pipelines, automated testing frameworks, and infrastructure‑as‑code to support reliable AI delivery.
- Ensure strong observability across AI workloads, including logging, tracing, token usage monitoring, drift detection, and model performance dashboards.
AI governance, compliance, and risk
- Partner with compliance, risk, and information security teams to ensure AI capabilities meet regulatory expectations within financial services (FCA, PRA, GDPR).
- Lead the implementation and ongoing compliance of ISO 42001 (AI Management Systems), embedding governance and documentation into engineering processes.
- Establish model governance practices such as audit trails, explainability documentation, bias testing, and human‑in‑the‑loop review processes.
- Own and evolve the responsible AI framework, covering data provenance, consent management, and model risk oversight.
Providing technical leadership
- Set the technical vision and roadmap for AI engineering at Send, evaluating emerging models, tooling, and techniques.
- Mentor and support engineers across the team, fostering a culture of experimentation, engineering excellence, and continuous learning.
- Represent AI engineering in cross‑functional planning, architecture discussions, and strategic stakeholder conversations.
The Skills and Experience Needed for the Lead AI Engineer Role
- Significant software engineering experience (typically 5+ years), with a strong focus on Python in production environments, including modern frameworks such as FastAPI or Starlette, dependency management, and robust testing practices.
- Proven experience building and shipping production services that integrate with public LLM APIs, including prompt design, agent or chain orchestration (e.g. LangChain, LlamaIndex, Semantic Kernel, or similar), and retrieval‑augmented generation (RAG) architectures.
- Strong understanding of LLM fundamentals, including tokenisation, context windows, embeddings, vector similarity search, and the trade‑offs between fine‑tuning and in‑context learning, alongside practical approaches to evaluating model performance.
- Hands‑on experience building cloud‑native AI/ML infrastructure on platforms such as AWS, Azure, or GCP, including serverless compute, managed containers, object storage, and scalable networking.
- Experience working within a regulated environment (financial services, insurance, banking, or fintech), with an understanding of how compliance, governance, and risk considerations influence engineering decisions.
- Solid data engineering fundamentals, including experience with SQL, columnar data formats such as Parquet or Arrow, modern ETL/ELT patterns, and data pipeline orchestration tools such as Airflow or Prefect.
- A track record of technical leadership, contributing to architecture decisions, setting engineering standards, reviewing code, and mentoring other engineers within a team.
Nice to have
- Experience working with open‑source or self‑hosted LLMs (such as Llama or Mistral) and model serving frameworks like vLLM, TGI, or Triton.
- Familiarity with LLM evaluation and prompt‑testing frameworks to systematically measure output quality across different use cases.
- Knowledge of advanced retrieval techniques such as hybrid search, re‑ranking, knowledge graphs, or structured information extraction.
- Experience designing multi‑agent systems, tool‑use patterns, or autonomous AI workflows in production environments.
- Experience in insurance, insurtech, or underwriting data domains (e.g. bordereaux, claims, or underwriting workflows).
- Awareness of ISO 42001 or experience contributing to an AI governance or management framework aligned with the standard.
- Contributions to open‑source AI/ML projects, technical publications, or active participation in the AI engineering community.
What’s on Offer – Life at Send
Health Insurance – Provided through AXA, covering medical, dental, optical, mental health, and therapies. Employees also have free access to Spill, offering confidential mental health support and therapy.
Life Insurance – Covers four times your basic salary, along with Income Protection for up to 36 months at 75% of salary, including rehabilitation support.
Pension Scheme – A salary sacrifice pension scheme through Royal London. Send contributes 8%, with a minimum employee contribution of 4%.
Time Off – 25 days of annual leave, plus public holidays. We also offer volunteering time and a dedicated wellness day.
Learning and Development – An annual budget via Learnerbly, providing access to books, courses, conferences, and other resources to support your growth.
We welcome applications from everyone, regardless of background, ethnicity, culture, gender identity, or other personal characteristics. We are committed to reviewing all applications fairly and do not discriminate based on race, ethnicity, colour, religion or belief, national origin, sexual orientation, age, marital or civil partnership status, family status, pregnancy or maternity, disability (visible or invisible), gender identity or expression, or any other legally protected status.
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