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Metro location and broad AI skill requirements increase competition despite seniority and niche LLM focus.
Core LLM and MLOps skills are transferable, but leadership and multi-agent specialization add moderate industry specificity.
Explicit 12–15 years plus mandatory LLM, ML, MLOps, and leadership skills create high shortlisting strictness.
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Lead end-to-end development and delivery of production-grade AI/ML/NLP solutions including LLMs and multi-agent systems.
Architect, optimize, and integrate RAG pipelines, multi-agent AI workflows, and cloud-native scalable AI systems with focus on performance, cost, and observability.
Mentor and guide ML engineers and data scientists while collaborating with cross-functional teams to drive AI product strategy and implementation.
12 to 15 years total professional experience.
5+ years of Machine Learning and NLP experience, including 2+ years with LLM-based applications and 1.5+ years with multi-agent AI systems.
Strong programming skills in Python; experience with PyTorch or TensorFlow required.
Location: Bengaluru; Full-time employment.
Experienced leader with demonstrated ability to architect and deliver complex AI systems at scale using LLMs, RAG, and multi-agent frameworks.
Deep hands-on expertise in NLP techniques including embeddings, transformers, prompt engineering, and fine-tuning workflows.
Proficient in building cloud-native, microservices-based AI applications with knowledge of CI/CD, MLOps, monitoring, and responsible AI practices.