Key Responsibilities

AI/ML Architecture

Design and implement scalable AI/ML architectures for enterprise applications

Lead end-to-end AI solution delivery from data pipelines to deployment and monitoring

Build reusable AI frameworks and accelerators

Generative AI Agentic AI

Develop and architect LLM-based applications

Design and implement RAG solutions using vector databases and semantic search

Build AI agents, tool-calling workflows, multi-agent systems, and MCP integrations

Develop conversational assistants, coding assistants, automation agents, and enterprise copilots

Machine Learning Solutions

Recommendation Systems

Demand Forecasting

Price Prediction

Customer Segmentation

Fraud Detection

Predictive Analytics

Search Relevance Ranking

Behavioral Analytics

Optimization Problems

Cloud MLOps

Lead AI implementations on GCP using Vertex AI, BigQuery, GKE, Cloud Run, Pub/Sub, Dataflow, and Vector Search

Establish MLOps best practices including model monitoring, experiment tracking, feature stores, CI/CD, drift detection, and automated retraining

Deploy scalable AI services using FastAPI, Docker, Kubernetes, and Microservices

Programming ML

Python

NumPy, Pandas, Polars

Scikit-learn, XGBoost

TensorFlow, PyTorch





Generative AI

Large Language Models (LLMs)

RAG Architecture

Prompt Engineering

Embedding Models

Semantic Hybrid Search

AI Agents Tool Calling

MCP Integrations

Frameworks

LangChain

LangGraph

LlamaIndex

CrewAI

AutoGen

Vector Databases

Pinecone

Weaviate

FAISS

Milvus

Elasticsearch

Vertex AI Vector Search

Cloud Infrastructure

Google Cloud Platform (GCP)

Docker

Kubernetes

GKE

Serverless Event-Driven Architectures

Preferred Experience

Retail, eCommerce, Financial Services, Analytics, Customer Experience, or Enterprise Automation domains

Experience with Vertex AI Search, Google Commerce Search, Dialogflow CX, OR-Tools

Knowledge of Responsible AI and Enterprise AI Governance

What You ll Drive

Enterprise AI Strategy Roadmap

Scalable AI/ML Platforms

Generative AI Adoption

Customer Personalization Automation

AI Engineering and MLOps Best Practices

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI/ML Architect (Bengaluru)
🏢 Codevian Technologies
📍 Bengaluru