Experience (10 to 15 years )
Key Responsibilities
- Architect and develop innovative generative AI solutions with a focus on scalability and efficiency on the Azure /AWS cloud platform. Implement and maintain containerized AI applications using Docker and manage deployments using Kubernetes. Design and set up observability frameworks for LLMs to monitor performance metrics, system health, and usage patterns. Collaborate with cross-functional teams to ensure seamless integration of AI capabilities into various products and services. Lead performance tuning, troubleshooting, and optimization of generative AI systems. Develop best practices for secure, scalable, and maintainable AI deployments on Azure/AWS. Guide and mentor a team of AI engineers in adopting and implementing cutting-edge technologies and practices. Stay updated with the latest advancements in AI, particularly in the areas of generative models and cloud computing. Advocate for responsible AI development, ensuring ethical considerations and privacy compliance are embedded in our AI systems.
Qualification A minimum of 10 years of hands-on experience in software development with a strong focus on AI and Azure / AWS cloud architectures. Solid programming skills in Python, with expertise in AI/ML frameworks and strong knowledge in Azure OpenAI / Bedrock Excellent knowledge in GenAI development related frameworks to develop and implement Generative AI based solutions. In-depth knowledge of Azure/AWS cloud services and management tools. Proficient with Docker and Kubernetes for orchestrating containerized applications. Demonstrable experience with implementing and monitoring Large Language Models. Experience with implementing CI/CD pipelines and familiarity with DevOps practices. Strong analytical and problem-solving skills, with the ability to lead complex technical initiatives.
Preferred Skills Azure/AWS certifications (e.g., Azure Solutions Architect, Azure Developer, Azure AI Engineer, AWS Solutions Architect, AWS Developer, AI Practitioner). Experience with LLM observability tools (e.g., Langfuse, Datadog, etc). Knowledge of machine learning model lifecycle management and MLOps principle. Knowledge of machine learning model lifecycle management and MLOps principle
Pay: ₹4,500,000.00 - ₹6,000,000.00 per year
Ability to commute/relocate:
- Bengaluru, Karnataka (Bengaluru Rural District): Reliably commute or planning to relocate before starting work (Required)
Application Question(s):
- LLM and RAG ,Gen AI Architect are mandatory requirements
Language:
Location:
- Bengaluru, Karnataka (Bengaluru Rural District) (Required)
Shift availability:
Work Location: In person
