MLOps Technical Architect

We are seeking an experienced MLOps Technical Architect to lead the architecture, design, and deployment of enterprise AI/ML, Generative AI, and Agentic AI solutions. The ideal candidate will have strong expertise in MLOps, cloud-native AI platforms, LLMs, RAG architectures, and AI agent frameworks, with the ability to deliver scalable, production-ready AI solutions.

• Strong programming experience in Python and Java.
• Hands-on experience with Agentic AI frameworks, including Google ADK, A2A, Lang Chain/Lang Graph, CrewAI, Semantic Kernel/Auto Gen, and OpenAI Agent SDK.
• Experience integrating Gemini Tools and Custom MCP (Model Context Protocol) Tools.
• Strong knowledge of Tensor Flow, PyTorch, and AutoML for machine learning model development.
• Hands-on experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Natural Language Processing (NLP).
• Experience designing and implementing RAG architectures, including data ingestion, retrieval, hybrid search, and response generation.
• Strong experience with Google Cloud Platform (GCP), Vertex AI, and Kubeflow.
• Experience in data preprocessing, feature engineering, and ML pipeline development.
• Proficiency with Git Hub for source control and version management.
• Experience in model development, testing, validation, deployment, and monitoring.
• Strong knowledge of databases including Oracle, DB2, PostgreSQL, Big Query, Cassandra, and Big Data platforms.
• Experience working in Agile/Scrum environments.

• GPU programming and performance optimization.
• GPU profiling and TensorRT optimization.
• Experience with vector databases and AI model optimization techniques.

• Collaborate with business and IT stakeholders to understand business requirements and identify AI/ML opportunities.
• Architect scalable AI/ML, MLOps, Generative AI, and Agentic AI solutions.
• Lead the design and development of machine learning models, AI pipelines, and intelligent agent workflows.
• Develop, optimize, and automate ML models, pipelines, and orchestration logic.
• Design and deploy LLM-powered applications, RAG pipelines, AI agents, and vector-based memory systems.
• Build integrations with enterprise systems using APIs, Gemini tools, and MCP-based integrations.
• Work closely with Data Scientists, ML Engineers, Dev Ops, and Software Engineering teams to ensure successful deployment and operational excellence.
• Drive technical architecture, infrastructure, tooling, and cloud strategy for AI platforms.
• Monitor solution performance, troubleshoot production issues, and implement continuous improvements.
• Provide timely project updates, technical guidance, and documentation to stakeholders and leadership.
• Identify opportunities for process automation and operational efficiency.
• Foster collaboration across cross-functional teams to ensure successful project delivery.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Experience designing enterprise-scale AI/ML and MLOps platforms.
• Familiarity with cloud-native AI deployment and CI/CD practices for machine learning.