ANSR is hiring for one of its clients:

About BRIT:

Brit India GCC is the heart of Brit Insurance’s innovation engine. Their team of highly skilled professionals specializes in Data Engineering, Platform Engineering, Full-Stack Web Application Development, Data Management, and Testing. Born in 1995 in London (UK), Brit Ltd. is a leading international general insurance and reinsurance group.

Boasting one of the largest and most diverse portfolios in Syndicate 2987, we hold an influential and respected presence at Lloyd's of London. Renowned for our innovative approach to commercial insurance and reinsurance, we at Brit are committed to securing an uncertain future with a hallmark of certainty.

A legacy of excellence, driving innovation and personalized service to create exceptional customer experiences.

The Lead AI Engineer will provide hands-on technical expertise and people management to deliver scalable, production-ready, end-to-end AI solutions that drive measurable business value. The role will help shape and deliver AI-powered applications that advance Brit’s Smarter Underwriting and Operational Simplification strategies, combining classical data science and machine learning with generative and agentic AI and low code/no-code AI tools. Working closely with AI/ML Engineers, Applied AI and Data Scientists, AI Solution Engineers, Data Engineers, AI QA Engineers, Product and Business teams across UK and India, the role helps deliver AI powered applications from opportunity discovery and requirements through prototyping, testing, deployment, adoption and post-implementation review.

This role also supports the responsible evolution of AI capability by defining what good looks like for specific use cases and evaluating AI system performance in real-world settings.

Principle Accountabilities :

- Design, build and deploy applications using statistical and machine learning methods, LLMs, RAG, agentic workflows and automation, while contributing production-quality code, APIs, integrations and reusable components.
- Lead discovery, solution design, prototyping, build, evaluation, testing, production deployment, change adoption and benefits review, making pragmatic build-or-buy and pro-code or low-code decisions.
- Set standards for architecture, code review, testing, CI/CD, MLOps/LLMOps, observability, reliability, cost and performance, ensuring solutions are supportable and scalable.
- Embed security, privacy, data governance, model risk, explain ability, human oversight and regulatory controls throughout the lifecycle, documenting decisions, limitations and operational controls.
- Manage, coach and develop a team across AI Solution Engineering, AI/ML Engineering, Applied AI Science and AI Data Science,



creating clarity of purpose and an inclusive, high-performing team environment.

Translate complex AI concepts into clear business choices, facilitate cross-functional decisions, and communicate progress, risks, trade-offs and realized outcomes to technical and non-technical audiences. Education, Qualifications, Knowledge, Skills and Experience :

Required education/experience:

- Bachelor’s Degree or higher in a STEM field.

Preferred education/experience:

- Master’s Degree or higher in a STEM field. Experience utilizing data science in a commercial environment.

Technical:

- Experience utilizing data science and machine learning with generative and agentic AI in a commercial environment, including demonstrable technical leadership and leading people, projects or multidisciplinary delivery teams.
- Proven delivery of AI-powered applications from ambiguous business problem to production operation, with evidence of measurable business impact and sustained adoption.
- Hands-on application of classical statistics, supervised and unsupervised machine learning, feature engineering, experimentation and model evaluation.
- Hands-on delivery of generative AI and agentic solutions, including prompt design, RAG, embeddings/vector search, tool or function calling, orchestration, structured outputs and failure handling.
- Experience selecting and combining pro-code and low-code/no-code approaches, including Microsoft Azure AI services and platforms such as Copilot Studio, Power Platform/Power Apps, Cytora or comparable products is desirable.
- Experience in a regulated, data-sensitive environment; insurance, reinsurance or the London Market is advantageous.
- Strong ability to translate between scientific and business language for non-technical stakeholders.

People leadership and ways of working:

- Build and connect Brit India’s AI community, fostering knowledge-sharing, reusable practices and capability development, while ensuring close collaboration and alignment with the AI Enablement and AI UW Labs teams across India and the UK.
- Set clear goals and accountabilities, allocate work across both teams and balance strategic delivery, experimentation, production support and colleague development.
- Conduct regular one-to-ones and performance reviews; provide timely, evidence-based feedback,



recognition and coaching; create individual capability and development plans.
- Mentor engineers and scientists through pairing, technical reviews and stretch opportunities; build depth across AI engineering, science, operations and domain knowledge.
- Address delivery or behavioral concerns constructively, resolve conflict fairly and promptly, and foster psychological safety, inclusion and effective cross-team collaboration.
- Support workforce planning, recruitment, onboarding, succession and capability development; create reusable standards and communities of practice across Brit.

Non-Technical:

- Investigative, analytical and problem-solving skills.
- Ability to quickly adapt to new methods, work under tight deadlines.
- Ability to work well within a team environment, participate in department/team projects and balance detail with departmental objectives.
- Strong oral and written communication skills, demonstrating the ability to convey technical terminology that is meaningful and well received.
- Ability to resolve conflict, foster teamwork and work collaboratively across different business areas.
- Data is a key capability to drive Brit’s ambition for digital, innovation, growth and efficiencies. Brit leads the market with respect to our data modernization journey, delivering on our vision to build a central, trusted, cost efficient, flexible, and scalable cloud native data platform that enables us to harness maximum value from internal and external data for Brit.
- Brit is active in advancing digital trading approaches, most notably with respect to Broker APIs. At Brit, we are designing a multi class of business headless API which connects Brits pricing and document generation to multiple global Broker platforms, Market Hubs, and enables bulk submission ingestion.
- Brit has launched its Underwriting Transformation journey advancing our capabilities deploying digital foundations for pricing and underwriter workbench. Brit’s recent modern Underwriting Platform is at the heart of this transformation agenda, with a focus on engineering, upskilling in python, exploring ingestion and analytics, we are actively delivering our digital future.
- Our market leading proprietary machine learning algorithm designed to accelerate the identification of post catastrophe property damage, based on the use of ultra-high-resolution imagery, allows Brit to accelerate service to its customers when they need it most, noted as the first enabler for virtual claims adjusting in the London market.
- We value continuous learning & exploration, encouraging our people to constantly evolve and take advantage of the best-in-class technology & tooling

📌 Lead AI Engineer-28772] (Bengaluru)
🏢 ANSR
📍 Bengaluru