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Popular technical PM title in a metro with niche AI requirements yields moderate competition.
Requires deep ML/LLM systems, MLOps, and enterprise deployment expertise, so background fit sensitivity is high.
Explicit 10-15 years plus mandatory ML/LLM, cloud, and architecture skills make filtering highly selective.
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Own the end-to-end technical architecture and solution design for enterprise-grade ML/LLM systems, ensuring scalability, security, and performance.
Define and implement solutions across application development, infrastructure, deployment, testing, and operations, including containerized and cloud-native environments.
Provide technical ownership throughout the solution lifecycle, including performance engineering, optimization, and on-call support for enterprise implementations and pilots.
10-15 years of relevant work experience in ML Systems Engineering or MLOps with hands-on exposure to deploying and operating LLM applications at scale.
Strong technical skills with ML/LLM systems, containers, Kubernetes, CI/CD, DevOps, and public cloud platforms (AWS, Azure, or GCP).
Experience with architecture and deployment for on-premises, hybrid, and cloud environments with emphasis on security, performance, and enterprise-grade non-functional requirements.
Location requirement: Pune, India.
Experienced in designing and delivering B2B enterprise AI/ML solutions supporting multiple deployment models including data-center and cloud.
Strong architectural and problem-solving skills with the ability to communicate complex technical concepts to diverse stakeholders.
Capable of independently driving technical ownership and collaborating effectively in high-complexity environments involving advanced AI models and autonomous engineering approaches.