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Mid-level ML/AI role in Bangalore with metro location and generalist MLOps requirements.
Highly specialized agentic AI, LLM, and MLOps expertise limits cross-industry transferability.
Explicit 6–8 years plus 5+ years generative AI and mandatory agentic AI/MLOps skills increases filter strictness.
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Design, build, and deploy agentic AI systems using LLMs, tool orchestration, and multi-agent workflows across multiple client engagements.
Translate ambiguous business problems into scalable and robust AI architectures, providing technical oversight to ensure alignment with design intent.
Prototype solutions, influence pre-sales, create solution blueprints, and set technical standards while remaining hands-on with coding and mentoring engineers and data scientists.
6–8 years of professional software engineering experience, including 5+ years hands-on with Generative AI and LLM-based production systems.
Degree required: BE/B.Tech/ME/M.Tech in Computer Science, IT, Electronics Engineering, Data Science, Machine Learning, AI Engineering or related field.
Strong experience building multi-agent/agentic AI systems, MLOps pipelines, retrieval augmented generation (RAG), vector databases, and AI system observability.
Proficiency in Python and core data science/ML libraries with practical skills in prompting, RAG, and integration of LLM systems with enterprise APIs.
Experienced in architecting enterprise-scale AI systems beyond individual model development, comfortable balancing strategy and delivery across simultaneous projects.
Operates with strong technical and architectural rigor, able to debug production AI issues and implement fixes securing system robustness.
Has some experience in client-facing roles, with mentoring junior team members and familiarity or interest in consulting environments; exposure to cloud AI platforms like Azure is advantageous but not mandatory.