3+ years hands-on experience in AI/ML, Generative AI, Intelligent Automation, or Agentic AI.
Strong Python programming skills.
Experience with AI/ML frameworks such as LangChain, MLflow, TensorFlow, PyTorch, or Scikit-learn.
Strong experience with LLMs, RAG, embeddings, semantic search, and vector-based retrieval.
Hands-on experience designing and deploying AI-powered applications, AI agents, or automation solutions.
Experience with Pandas, NumPy, Spark, data engineering, feature engineering, and data processing.
Strong SQL skills and experience working with large enterprise datasets.
Strong understanding of AI architecture, orchestration frameworks, enterprise integrations, governance, security, and Responsible AI.
Experience with MLOps, including model versioning, experiment tracking, and pipeline orchestration.
Strong data analysis, business process assessment, problem-solving, and analytical skills.
Excellent communication skills with the ability to explain AI concepts to technical and non-technical stakeholders.
Ability to collaborate with cross-functional business and technology teams.
Bachelor s degree in Computer Science, Engineering, Data Science, or a related quantitative field.
Agentic AI frameworks, prompt engineering, and workflow orchestration.
LLM/foundation model training, fine-tuning, and optimization.
Vector databases, semantic indexing, and enterprise knowledge retrieval.
Experience identifying AI/GenAI opportunities from application backlogs.
Experience developing business cases, implementation roadmaps, and value/ROI metrics.
Enterprise AI transformation, application modernization/rationalization, or digital transformation.
Microservices, APIs, event-driven architecture, and CI/CD.
Tableau, Power BI, or Looker.
Background in NLP, information retrieval, or intelligent automation.
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