AI/ML Architect

Job Description : Key Responsibilities:  Participate in developing Generative AI & Traditional AI Platform Capabilities on enterprise on- prem and cloud platforms.  Responsible for AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI, Azure ML)  Collaborating with Data scientist to optimize the scoring pipeline.  Building automation capabilities to deploy ML Models and LLM Models on the enterprise on- prem platform and cloud platform.  Build and Deploy capabilities for automating model scoring/Inferencing of ML models and LLMs.  Build and Deploy capabilities for data pipeline deployment standardization and model consumption by multiple LOBs.  Collaborate with product owners, devOps team, data scientists, support teams to define and drive end to end model scoring pipelines.  Participate in day-to-day standups for platform capability build.  Provide SME guidance for data science teams on software engineering principles, model deployments, platform capabilities.  Drive AI use case delivery end to end collaborating with Data scientists, Data Engineers, LOB Technology using standardized platform processes and capabilities.  Support Production Issues partnering with production support. Key Requirements:  5 years of Python experience  5 years of big data experience needed (Big Query, Hadoop)  3 years of experience in AIML area (MLOps)  2 years of experience in developing APIs using Python/FastAPI.  1 year of Document AI, Agent Builder/GCP search/conversation / Dialogflow – Nice to have  Good to have 1year of experience in LLM, Generative AI (developing capabilities or dev/ops)  Good to have Experience in developing of API on GCP/Azure/API Gateways  Good to have 1year of experience in Vector Database, Model Development would be an added benefit.