AI / ML Ops Architect

Job Title: AI / ML Ops Architect

Location : Remote

Full Time

Job Description

Must Have Technical/Functional Skills

Technical Skills -

• Programming Languages: Python, Java
• Agentic AI : Google ADK, A2A, LangChain/LangGraph, CrewAI, Semantic Kernel/Autogen and Open AI Agentic SDK
• Tool Integration: Gemini Tools, Custom MCP tools
• Machine Learning Frameworks: Experience with TensorFlow, PyTorch and AutoML.
• Generative AI: Hands-on experience with generative AI models, RAG (Retrieval-Augmented Generation) architecture, and Natural Language Processing (NLP).
• Cloud Platforms: Google Cloud Platform (GCP), Vertex AI and Kubeflow
• Data Engineering: Proficiency in data preprocessing and feature engineering.
• Version Control: Experience with GitHub for version control.
• Data Science Practices: Skills in building models, testing/validation, and deployment.
• Databases: DB2, Oracle, BigQuery, BigData, Cassandra, PostGRES
• Collaboration: Experience working in an Agile framework.
• RAG Architecture: Experience with data ingestion, data retrieval, and data generation using optimal methods such as hybrid search.
• Good to Have: Knowledge in GPU programming, GPU profiling, GPU optimizations & TensorRT

Functional Skills -

• Experience working with customers in Retail Domain
• Knowledge in Retail Pricing functionalities is a plus

Roles & Responsibilities

• Meet with IT and Business teams to understand the requirements and opportunities
• Architect systems for AI/ML, agent-based AI workflows.
• Lead the design and development of AI/ML, ML Ops & Agentic AI solutions
• Develop and optimize ML models, pipelines, and orchestration logic
• Deploy AI/ML Models, LLM-based pipelines, agent orchestration, and vector-based memory systems
• Work closely with data scientists, ML engineers, DevOps, and software engineers to ensure seamless integration and deployment of solutions
• Drive technical strategy, tooling, and infrastructure decisions.
• Provides management with timely communication on status & utilizes appropriate tools and/or develops custom solutions as required to meet objectives.
• Identifies areas for process improvement.
• Maintains appropriate communication within the team and across various teams (i.e., internal and external).