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.
Required Skills
Technical Skills
- Strong programming experience in Python and Java.
- Hands-on experience with Agentic AI frameworks, including Google ADK, A2A, LangChain/LangGraph, CrewAI, Semantic Kernel/AutoGen, and OpenAI Agent SDK.
- Experience integrating Gemini Tools and Custom MCP (Model Context Protocol) Tools.
- Strong knowledge of TensorFlow, 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 GitHub for source control and version management.
- Experience in model development, testing, validation, deployment, and monitoring.
- Strong knowledge of databases including Oracle, DB2, PostgreSQL, BigQuery, Cassandra, and Big Data platforms.
- Experience working in Agile/Scrum environments.
Good to Have
- GPU programming and performance optimization.
- GPU profiling and TensorRT optimization.
- Experience with vector databases and AI model optimization techniques.
Functional Skills
- Experience working with clients in the Retail domain.
- Knowledge of Retail Pricing processes and merchandising solutions is an advantage.
Roles and Responsibilities
- 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, DevOps, 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.
Preferred Qualifications
- 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.
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