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Mid-level role in Bangalore at a known financial firm but niche agentic AI skills reduce general applicant pool.
Specialized agentic AI and enterprise deployment skills are transferable yet still require strong domain-specific expertise.
Explicit 5–10 years plus many mandatory LLM, engineering, and cloud skills make shortlisting highly selective.
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Design, develop, and productionize agentic AI applications employing planning, reasoning, routing, multi-agent collaboration, and workflow orchestration.
Build and optimize AI solutions integrating LLMs, Generative AI models, APIs, databases, and enterprise tools with emphasis on scalability, reliability, and evaluation.
Collaborate cross-functionally with data scientists, engineers, and platform teams to translate business requirements into measurable, secure, and operational AI systems.
5-10 years of professional experience with strong hands-on expertise in Python-based AI/ML or software development.
Degree required: BS, B.Tech, or Master’s in Computer Science, Engineering, Data Science or related field.
Proven experience in developing LLM/Generative AI applications including prompt engineering, RAG techniques, and use of agent frameworks such as LangChain or equivalent.
Hands-on experience with cloud platforms (Azure or AWS) and deploying AI applications via APIs, containers, and CI/CD pipelines.
Experienced in designing complex multi-step agentic AI workflows and integrating diverse enterprise systems with LLMs and AI tools.
Skilled in evaluation methodologies for agentic AI systems, including task accuracy, latency, cost, and reliability metrics.
Able to lead technical guidance and collaborate with cross-functional teams in regulated or enterprise environments with focus on secure, scalable AI production systems.