Description

Key Responsibilities

Lead architecture and design of Agentic AI, GenAI, and AI Ops solutions Define end-to-end AI architecture, including integration patterns and scalable frameworks Design and develop AI agents, orchestration workflows, and autonomous systems Integrate AI solutions with enterprise platforms, APIs, and cloud ecosystems Establish AI governance, security guardrails, and compliance frameworks Translate business requirements into scalable AI-driven solutions with measurable outcomes Drive AI roadmap, MVP strategy, and production readiness Implement risk management and AI control tower processes Provide technical leadership and mentor AI/ML engineering teams Collaborate with stakeholders, architects, and cross-functional teams Required Skills Strong experience in Agentic AI / Autonomous AI Systems Hands-on with Generative AI (LLMs, RAG, prompt engineering) Experience with AI orchestration frameworks (LangChain, Semantic Kernel, etc.) Proficiency in Python and AI/ML frameworks Experience with cloud platforms (AWS / Azure / GCP) Strong understanding of API integrations and microservices architecture Knowledge of AI governance, security, and compliance Experience with AI Ops / MLOps pipelines Excellent stakeholder communication and solutioning skills Preferred Skills Experience in enterprise AI transformation programs Knowledge of multi-agent systems and decision intelligence Exposure to vector databases and RAG architectures Familiarity with DevOps / CI-CD for AI solutions

Key Skills

Education

Bachelor's degree