AI Engineer

Job Summary

Job Title- AI Engineer; Position type- Full Time; Work Location- Bangalore, Whitefield; Working style- Hybrid; Cab Facility- Yes; Required education and certifications critical for the role- Any Graduate or Post-Graduate (full time); Required years of experience - 10+ years of relevant experience.

Aon is in the business of better decisions. At Aon, we shape decisions for the better to protect and enrich the lives of people around the world. As an organization, we are committed as one firm to our purpose, united through trust as one inclusive, diverse team and we are passionate about helping our colleagues and clients succeed.

General Description of Role

Aon is looking for an experienced AI Platform Engineer to join our global Cloud Enablement and Platform Engineering team. You will play a key role in designing, building, and scaling the platforms, tooling and frameworks that enable advanced AI/ML workloads across our cloud environment that solves real business problems for Aon s global operations at scale. You will work across our multi-cloud estate - Azure, GCP, AWS, and Databricks - where your expertise will directly influence how we deliver secure, scalable, and innovative solutions. You ll be a team player with strong interpersonal and communication skills, comfortable collaborating with diverse cross-functional teams to solve complex challenges and help shape the technical direction of a platform that will transform how AI is leveraged within Aon. You will take a hands-on approach to the provisioning of models and vector infrastructure across platform engineering, distributed systems, and modern Cloud AI/ML and Data infrastructure, consistently demonstrating your strong track record in delivering high-quality, reusable, outcome-focused solutions with the appropriate automation, guardrails, observability and cost governance.

Job Responsibilities

• Design, build, and operate the shared platform capabilities - golden paths, reusable pipelines, and provisioning patterns - that enable engineering and data teams to adopt AI/ML and Generative AI safely at scale.
• Build and maintain CI/CD pipelines and Infrastructure as Code (Terraform, Azure DevOps, GitHub Enterprise/Actions) for provisioning and managing AI infrastructure, including model endpoints, vector stores, compute, and GPU environments.
• Partner with Data engineering, AI engineering, and Product teams to define standards, guardrails, and self-service tooling for LLM, RAG, and agentic workloads - e.g. model/LLM gateways, vector database provisioning, and evaluation harness templates.
• Provide platform-level support for MLOps/LLMOps practices: model registries, model serving infrastructure, monitoring and observability, cost management, and responsible AI guardrails (PII redaction, prompt-injection defences, content filtering).
• Evaluate, integrate, and operationalize cloud-native AI services - Azure AI Foundry/OpenAI Service, AWS Bedrock/SageMaker, GCP Vertex AI, and Databricks Mosaic AI - into a unified, governed internal platform.
• Promote and enforce standard cloud and AI platform methodologies, processes, and tools that ensure compliance with architectural and security standards, which you will also help define.
• Build automation that enforces security, compliance, and cost governance for AI workloads across the multi-cloud estate, tying infrastructure spend to consumption.
• Act as a technical advisor to solution lines transitioning to or scaling AI-enabled cloud-based patterns, providing hands-on support and guidance.
• Lead by example and mentor engineers across the organization and geographies on AI platform patterns, designs, and engineering practices.
• Stay current with the fast-evolving AI and platform engineering landscape, evaluating new tools, models, and frameworks for enterprise-wide adoption.
• Champion the adoption of AI-assisted software engineering tools such as Claude Code and GitHub Copilot across engineering teams, establishing best practices, guardrails, and governance for their use.

Skills / Competencies Required

• 10+ years experience in cloud or platform engineering, ideally providing technical engineering, consulting, and operational support, with recent hands-on experience enabling AI/ML or GenAI workloads.
• Detailed understanding of and hands-on experience with at least two of Azure, GCP, AWS - working experience with Databricks highly desirable.
• Strong working experience with Terraform, PowerShell/Python, and other scripting/automation languages and techniques.
• Experience with DevOps approaches and CI/CD tooling for cloud and AI infrastructure, with particular focus on Azure DevOps and GitHub Enterprise/GitHub Actions.
• Experience integrating or supporting cloud AI/ML platforms such as Microsoft Foundry, GCP Vertex AI, AWS Bedrock/SageMaker, or Databricks Mosaic AI.
• Familiarity with containerization and orchestration frameworks (Docker, Kubernetes, AKS/EKS/GKE, Container Apps, ECS Fargate).
• Practical, hands-on use of AI-assisted development tools such as Claude Code, GitHub Copilot, or similar in day-to-day engineering work.
• Detailed understanding and experience with cloud security controls, and knowledge of security scanning tools (e.g. Wiz).
• Strong Python programming skills and experience with ML frameworks (PyTorch).

Qualifications

• Education: Bachelors or Master s degree in computer science, AI/ML, Data Science, or a related field
• AWS/Azure/GCP/Databricks AI/ML certified preferred
• Hashicorp Terraform / Microsoft DevOps Engineer certified desirable

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.