Senior AI / GenAI Engineer

Experience: 7 to Not Available years

Location: Bangalore, India

Skills: Microsoft Azure, Kubernetes, ML workloads, Generative AI, agentic workflows, MLOps, Azure Databricks, OpenAI, Google Gemini, LangGraph, Apache Kafka, AsyncAPI, real-time inference, batch inference, CI/CD, production support

Job Summary
We are seeking a Senior AI / GenAI Engineer with 7+ years of experience to lead the design, development, and deployment of enterprise‑scale AI and Generative AI solutions on Microsoft Azure. The role requires strong expertise in cloud‑native architectures, Kubernetes‑based ML workloads, GenAI, agentic workflows, and MLOps, along with the ability to drive technical decisions and mentor teams.

Key Responsibilities
• Lead the design, development, and deployment of AI solutions on Microsoft Azure using cloud‑native architectures
• Build, run, and optimize AI/ML workloads on Azure Kubernetes Service (AKS) for production use
• Architect and integrate AI solutions with Azure Databricks for large‑scale feature engineering and data pipelines
• Develop production‑grade Generative AI applications using OpenAI models and Google Gemini
• Design and implement agentic AI workflows using LangGraph for multi‑step reasoning and orchestration
• Build event‑driven AI services using Apache Kafka
• Design, document, and maintain asynchronous APIs using AsyncAPI specifications
• Implement and manage scalable inference services for both real‑time and batch AI use cases




• Apply and mature MLOps practices, including model deployment, versioning, monitoring, and observability
• Lead efforts to optimize AI systems for performance, scalability, reliability, and cost efficiency
• Collaborate closely with Data Scientists, Data Engineers, Platform, and DevOps teams
• Ensure adherence to security, governance, and enterprise compliance standards
• Provide technical guidance, code reviews, and architectural direction to junior engineers
Skill Requirements
• 7+ years of experience in software engineering / platform engineering / AI systems
• Strong hands‑on experience with Microsoft Azure for AI and data workloads
• Proven experience deploying ML workloads on Azure Kubernetes Service (AKS)
• Solid expertise in Azure Databricks for data processing and feature engineering
• Hands‑on experience building Generative AI applications using OpenAI and Google Gemini
• Experience designing agentic systems with LangGraph
• Strong understanding of event‑driven architectures using Apache Kafka
• Experience designing asynchronous APIs with AsyncAPI
• Strong understanding of real‑time and batch inference architectures
• Deep knowledge of MLOps, CI/CD pipelines, model monitoring, and production support
Enterprise & Leadership Skills
• Ability to work independently and own end‑to‑end AI solutions
• Robust collaboration skills across data, engineering, and platform teams
• Experience working in large‑scale, enterprise environments

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