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Strong Tier-1 employer, metro locations, and popular AI/ML engineering title drive high competition.
Specialized ML/MLOps skills transfer across industries, but financial-services regulatory knowledge increases domain specificity.
Explicit 8+ years, mandatory ML systems experience, and extensive tech stack and cloud/Kubernetes requirements make filtering strict.
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Design, build, and own core AI/ML subsystems such as agentic workflows, LLM applications, evaluation pipelines, and MLOps tooling at enterprise scale.
Deliver secure, scalable, production-grade AI solutions aligned with architectural vision while mentoring junior engineers.
Collaborate cross-functionally to define software requirements, ensure integration, and lead technical delivery impacting the entire business function.
Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related discipline.
8+ years software engineering experience with at least 3 years building AI/ML systems, scalable ML infrastructure, or model serving platforms at enterprise scale.
Proficiency in Python (FastAPI, asyncio) and/or Go/Java with experience building high-throughput, low-latency APIs and microservices.
Role based in Bengaluru or Pune; Work Experience Required: Explicitly 8+ years with 3+ years in AI/ML systems.
Experienced in developing complex agentic AI systems, multi-agent orchestration, and LLM applications using modern frameworks and technologies.
Strong background in distributed systems, cloud (AWS), containerization (Docker, Kubernetes), CI/CD, and infrastructure-as-code for scalable production environments.
Capable of leading cross-disciplinary teams with operational ownership of AI system delivery and risk management in a regulated enterprise environment.