Gallagher
Senior AI Engineer
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Colombo, Sri Lanka
Work mode:
Onsite
Published on:
10 September 2026
What they need
Introduction At Gallagher, we help clients face risk with confidence because we believe that when businesses are protected, they’re free to grow, lead, and innovate. You’ll be backed by our digital ecosystem: a client-centric suite of consulting tools making it easier for you to meet your clients where they want to be met. Advanced data and analytics providing a comprehensive overview of the risk landscape is at your fingertips. Here, you’re not just improving clients' risk profiles, you’re building trust. You’ll find a culture grounded in teamwork, guided by integrity, and fueled by a shared commitment to do the right thing. We value curiosity, celebrate new ideas, and empower you to take ownership of your career while making a meaningful impact for the businesses we serve. If you’re ready to bring your unique perspective to a place where your work truly matters; think of Gallagher.
Overview We’re looking for a Senior AI Engineer to join our Information Technology Systems Delivery team in Colombo, Sri Lanka.
In this role, you’ll help turn business challenges into practical AI solutions that create measurable value. You’ll work across the full lifecycle of AI-enabled products and services, from shaping use cases and defining requirements through to development, deployment, support and continuous improvement. You'll collaborate with technology teams, business stakeholders, architects, security specialists and data professionals to build AI capabilities that are secure, maintainable and aligned with responsible AI principles.
This role is ideal for someone who enjoys combining software engineering expertise with modern AI technologies to improve business processes, automate tasks, and support smarter ways of working.
How You'll Make An Impact You’ll work closely with colleagues across the business to identify opportunities where AI can make a meaningful difference. From helping shape new ideas through to delivering production-ready solutions, you'll engineer AI applications, integrations and workflows that solve real business problems and support better outcomes.
You'll play an important role in building reliable and sustainable AI capabilities, ensuring they meet quality, security and governance standards while remaining practical and easy to support. As AI solutions move into production, you'll help monitor performance, investigate issues, improve reliability and maintain technical roadmaps that keep solutions effective over time.
You’ll also support the growth of engineering capability across the team by sharing knowledge, helping colleagues develop their skills, and contributing to a culture of continuous learning and improvement.
Key areas you'll contribute to include:
- Designing, developing and supporting AI-enabled applications, services and integrations
- Building APIs, automation solutions and AI-assisted workflows
- Working with cloud platforms and modern engineering practices to deploy and operate solutions
- Supporting digitalisation, process improvement and automation initiatives across the business
- Helping ensure AI solutions are delivered responsibly, securely and in line with enterprise standards
About You Here’s what you’ll bring to the role:
- Experience designing, building, testing and supporting AI-enabled applications and services across the full solution lifecycle
- Experience developing software using one or more of the following technologies: Python, C#/.NET or Java
- Ability to design and build APIs, automation solutions and data processing services used in production environments
- Experience developing modern web applications using React or Angular
- Understanding of generative AI, machine learning concepts and AI-assisted workflows
- Ability to assess business challenges and translate them into practical AI use cases with measurable outcomes
- Knowledge of AI risks including data protection, model behaviour, bias, explainability, auditability and responsible AI practices
- Experience deploying and supporting applications on cloud platforms such as Microsoft Azure or AWS
- Familiarity with CI/CD pipelines, infrastructure as code and DevOps practices
- Experience monitoring production services, investigating incidents and managing technical improvements
- Understanding of secure software engineering practices, including identity management, access control, secrets management and vulnerability management
- Experience working with SQL and/or NoSQL data technologies
- Experience designing and consuming REST APIs, web services and event-driven integrations
- Understanding of RAG patterns, vector search, embeddings, prompt engineering, evaluation techniques and AI guardrails
- Ability to explain technical concepts clearly to colleagues with different levels of technical knowledge
- Experience working within Agile delivery teams and collaborating with architecture, security, testing, support and data teams
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
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