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Tier-1 bank and Pune metro increase applicant density, but seniority and niche AI skills moderately limit competition.
Specialized ML/AI, LLMs, and agentic AI integration require domain-specific expertise, limiting cross-industry transferability.
Explicit 10+ years, expert Python, LLM/MCP experience, and deployment/infra requirements make filters highly stringent.
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Design, develop, optimize, and maintain scalable ETL processes and data pipelines primarily using Python and SQL to support data warehousing and analytics needs.
Develop and implement AI-driven solutions, including engineering model context protocols (MCPs) and integrating large language models (LLMs) within agentic AI systems.
Lead the creation and maintenance of robust APIs and ensure operational stability, security, and resiliency of AI applications following best practices including CI/CD and agile methodologies.
Minimum 10+ years of hands-on application development experience.
Strong proficiency in Python (including frameworks like FastAPI, Flask, PySpark) and advanced SQL/PLSQL skills with Oracle/MySQL/Postgres/MongoDB.
Deep understanding and practical experience with AI concepts, including knowledge representation, automated planning, multi-agent systems, and relevant AI frameworks (e.g., Google ADK, LangChain).
Hands-on experience with Docker, OpenShift, microservices, API-first design, CI/CD pipelines, and software development best practices.
Experienced in designing and executing scalable enterprise AI and data solutions with strong system design and architecture skills.
Comfortable integrating advanced AI models such as ChatGPT, Claude, Gemini, and Llama into operational systems and developing AI model protocols.
Strong strategic focus on building flexible, robust, and secure AI and data infrastructure using modern technologies, architectures, and agile processes.