AI Engineer

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 : Responsibilities of this role include: 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). Highly Desirable Experience building or supporting RAG pipelines, vector databases (Pinecone, Weaviate, FAISS), or agent orchestration frameworks (LangChain, LangGraph, LlamaIndex). Strong Python programming skills and experience with ML frameworks (PyTorch, TensorFlow) Experience with MLOps/LLMOps practices — model monitoring and observability, evaluation harnesses, and guardrail/responsible AI implementation. Experience with native cloud infrastructure provisioning frameworks (Azure ARM/Bicep, AWS CloudFormation/SAM) alongside Terraform, including modules for AI-specific services. Experience with GPU orchestration, distributed training infrastructure, or scalable model serving. Competencies Excellent written and oral communication skills with the ability to collaborate effectively across multiple teams Able to work independently and in a self-directed manner with the ability to translate and solve business problems. Solution- and detail-orientated; strong analytical and experimental problem-solving mindset. Customer-focused; an effective collaborator with the ability to influence and enable other engineering teams rather than working in isolation. Excellent technical skills spanning cloud platforms, infrastructure, networking, security, and AI/ML platform patterns. Curiosity and continuous learning given the fast-moving AI and cloud platform landscape. Ability to multitask and prioritize activities to deliver desired outcomes. Education: Bachelor's 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 HOW WE SUPPORT OUR COLLEAGUES In addition to our comprehensive benefits package, we are proud to be an equal opportunity workforce. At Aon, we believe a diverse workforce is an innovative workforce. Our agile, inclusive environment allows colleagues to manage their wellbeing and work/life balance while empowering you to be your authentic self. Furthermore, all colleagues enjoy two “Global Wellbeing Days” each year, encouraging them to take time to focus on themselves. We offer a variety of workstyle options through our Smart Working model, but we also recognize that flexibility goes beyond just the place of work... and we are all for it! Our continuous learning culture inspires and equips colleagues to learn, share and grow, helping them achieve their fullest potential. As a result, Aon colleagues are more connected, more relevant and more valued. #LI-RK2 2586881Job 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 : Responsibilities of this role include: 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). Highly Desirable Experience building or supporting RAG pipelines, vector databases (Pinecone, Weaviate, FAISS), or agent orchestration frameworks (LangChain, LangGraph, LlamaIndex). Strong Python programming skills and experience with ML frameworks (PyTorch, TensorFlow) Experience with MLOps/LLMOps practices — model monitoring and observability, evaluation harnesses, and guardrail/responsible AI implementation. Experience with native cloud infrastructure provisioning frameworks (Azure ARM/Bicep, AWS CloudFormation/SAM) alongside Terraform, including modules for AI-specific services. Experience with GPU orchestration, distributed training infrastructure, or scalable model serving. Competencies Excellent written and oral communication skills with the ability to collaborate effectively across multiple teams Able to work independently and in a self-directed manner with the ability to translate and solve business problems. Solution- and detail-orientated; strong analytical and experimental problem-solving mindset. Customer-focused; an effective collaborator with the ability to influence and enable other engineering teams rather than working in isolation. Excellent technical skills spanning cloud platforms, infrastructure, networking, security, and AI/ML platform patterns. Curiosity and continuous learning given the fast-moving AI and cloud platform landscape. Ability to multitask and prioritize activities to deliver desired outcomes. Education: Bachelor's 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 HOW WE SUPPORT OUR COLLEAGUES In addition to our comprehensive benefits package, we are proud to be an equal opportunity workforce. At Aon, we believe a diverse workforce is an innovative workforce. Our agile, inclusive environment allows colleagues to manage their wellbeing and work/life balance while empowering you to be your authentic self. Furthermore, all colleagues enjoy two “Global Wellbeing Days” each year, encouraging them to take time to focus on themselves. We offer a variety of workstyle options through our Smart Working model, but we also recognize that flexibility goes beyond just the place of work... and we are all for it! Our continuous learning culture inspires and equips colleagues to learn, share and grow, helping them achieve their fullest potential. As a result, Aon colleagues are more connected, more relevant and more valued. #LI-RK2