AI Engineer

What you'll be doing:

· Build and deliver production-grade Agentic AI solutions that solve real client problems and create measurable business value.

· Design, develop and deploy autonomous and multi-agent AI systems using hyperscaler AI platforms.

· Implement AI-powered assistants, agents and intelligent workflow solutions leveraging RAG and advanced orchestration techniques.

· Write, test and maintain production-quality code for AI agents, integrations and orchestration pipelines.

· Apply software engineering best practice throughout the development lifecycle, including code quality, testing, CI/CD and version control.

· Work closely with architects, business and delivery teams to integrate AI capabilities into enterprise applications, workflows and operating models.

· Translate solution designs into working, deployable AI systems, contributing to design decisions along the way.

· Troubleshoot, optimise and scale AI agent and RAG implementations in live enterprise environments.

· Work within Agile delivery methodology, contributing to sprint planning, estimation and iterative delivery cycles.

· Stay current with emerging AI tools, frameworks and techniques, applying new approaches where they add value.

· Provide technical leadership and guidance to junior engineers on AI engineering best practice.

What experience you'll bring:

· Minimum 4–5 years' experience in software or AI engineering, including at least 2 years hands-on with Generative AI and Agentic AI solutions.

· Proven experience building and deploying Agentic AI solutions on hyperscaler cloud platforms (AWS, Microsoft Azure and/or Google Cloud).

· Strong Python skills, with experience building production-grade AI agents, APIs and integrations.

· Hands-on coding experience implementing AI agents, multi-agent systems, intelligent workflow automation, RAG architectures and AI-powered assistants in enterprise environments.

· Strong knowledge of agentic frameworks and orchestration technologies such as LangGraph, AutoGen, CrewAI, Agent Development Kit (ADK) or equivalent.

· Practical experience with AI engineering platforms across hyperscalers, such as AWS Bedrock, Azure AI Foundry and Google Vertex AI.

· API and integration development experience, connecting AI solutions to enterprise systems and data sources.

· Experience implementing observability for AI systems (logging, monitoring, tracing) to support reliable production operation.

· Solid software engineering fundamentals (APIs, CI/CD, testing, version control) applied to AI/ML systems.

· Experienced working within Agile delivery methodology (e.g., Scrum, Kanban).

· Comfortable engaging with technical stakeholders and explaining implementation choices clearly.

· Strong communication and consulting skills with experience working in customer-facing roles, comfortable engaging directly with clients on requirements and solution delivery.

· Experience and business domain knowledge within the insurance and / or other regulated sectors with an understanding of industry challenges, processes and regulatory considerations.

· Strong problem-solving skills, a builder's mindset, and a passion for hands-on innovation and continuous learning.

· Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, Business Technology, or a related discipline, or equivalent combination of education and experience.

· Relevant certifications are advantageous (e.g., AWS Certified Solutions Architect/Developer Associate, Azure AI Engineer Associate, Google Cloud Professional ML Engineer).