Senior Technical Lead
Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Artificial Intelligence · Data Engineering
In short
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 in Bangalore. The role focuses on cloud-native architectures, Kubernetes, GenAI, agentic workflows, and MLOps, requiring strong technical leadership and mentoring abilities.
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.
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
- Strong collaboration skills across data, engineering, and platform teams
- Experience working in large-scale, enterprise environments
Benefits
- Supercharge your potential
- Find your career
- Find your spark
- A place that knows that helping its customers stay on top starts by putting its people first.
#AI#GenAI#Cloud#Azure#Kubernetes#MLOps