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Niche agentic AI specialization lowers competition despite strong employer brand.
Core ML, MLOps, and cloud skills transfer well, but agentic AI specialization limits portability across industries.
Explicit 7+ years, 2+ years agentic AI requirement and mandatory tech stack make filters strict.
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Lead evaluation, recommendation, and implementation of autonomous AI tools, frameworks, and cloud platforms (AWS preferred) for scalable deployments.
Design and optimize autonomous AI architectures including multi-agent systems and LLM-driven decision engines, integrating emerging research into production.
Develop architectural documentation, conduct rigorous system validation including stress and bias testing, and collaborate with stakeholders to align AI initiatives with strategic goals.
7+ years progressive experience in AI/ML, including 2+ years focused on architecting autonomous/agentic AI systems or ML workflows.
Proficiency in Python and experience with autonomous AI tools/frameworks such as LangChain, Autogen, CrewAI, or custom agentic frameworks.
Experience with cloud AI platforms, especially AWS services (redis, lambda, eks, postgres), and knowledge of Google Cloud Vertex AI and IDEs.
Experience with MLOps pipelines (Kubeflow, MLflow) and designing scalable AI agent deployment strategies in production environments.
Technically strong AI Architect with direct experience architecting and deploying production-grade autonomous AI/agentic systems
Comfortable integrating cutting-edge R&D into scalable AI solutions and capable of documenting and communicating complex AI architectures to varied stakeholders.
Experienced in cloud-native AI infrastructure with a strategic mindset on AI system resilience, compliance, and operational excellence.