Source description
About the role
This person would help to drive the AI strategy for solving business problems, implement AI, GenAI, Agentic AI for automation, legacy software modernization, engg lifecycle integration and for productivity enhancements and tooling.
Required Qualifications
8+ years of professional experience in AI, machine learning, or software engineering with AI focus
Deep expertise in at least one of: Generative AI, LLMs, agentic AI systems, or modern AI frameworks
Strong programming skills in Python, Java, Go, or similar languages
Demonstrated experience building and deploying production-grade AI systems
Proficiency with popular AI/ML frameworks (TensorFlow, PyTorch, LangChain, AutoGen, etc.)
Experience with cloud platforms (AWS, Azure, Google Cloud) and containerization (Docker, Kubernetes)
Understanding of software architecture, design patterns, and enterprise system integration
Knowledge of data engineering, data pipelines, and relevant data governance practices
Familiarity with DevOps, MLOps, and CI/CD practices
Technical Competencies
AI/ML Technologies : Deep learning, NLP, computer vision, reinforcement learning, foundation models
GenAI Tools : ChatGPT, Claude, Gemini, open-source models; API integration and deployment
Agentic AI : Agent frameworks, multi-step reasoning, tool integration, agent orchestration
Software Architecture : Microservices, serverless computing, distributed systems, system design
Data Engineering : Data pipelines, ETL processes, data quality, feature engineering
DevOps & MLOps : Model versioning, experiment tracking, monitoring, deployment automation
Analytics & Evaluation : Metrics definition, model evaluation, performance benchmarking
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