Python + Gen AI Automation

Role : Python + Gen AI Automation
Experience : 6 to 10 years
Location : Chennai, Kolkata, Hyderabad, bangalore,Pune, Delhi
Key skills : Python development and Generative AI expertise to build and scale AI-first platforms and applications. The role focuses on developing and operationalizing GenAI solutions on Google Cloud Vertex AI, while also integrating capabilities across AWS and OpenAI ecosystems.
Desired Competencies (Technical/Behavioral Competency)
Must-Have
Python Dev (KARAT Completion)
GenAI App Dev ( LangChain, LangGraph, RAG Pipelines)
GCP/AWS/OpenAI Platform Experience
Core Technical Skills
Strong expertise in Python (mandatory)
Experience building backend services using:
FastAPI / Flask
5–12 years in software/platform engineering ---- Python
Minimum 2+ years in GenAI/LLM-based system development (mandatory)
Bachelor’s/Master’s in Computer Science, AI, or related field
Good-to-Have
GenAI & Framework Expertise (Mandatory)
Hands-on experience with:
LangChain
LangGraph
Strong expertise in:
RAG (Retrieval-Augmented Generation)
Prompt engineering
LLM orchestration
Experience integrating:
Vertex AI / OpenAI / AWS Bedrock
Cloud & Platform Experience (Mandatory)
Strong experience with GCP (Vertex AI preferred)
Working knowledge of AWS and OpenAI platforms
Experience with:
Docker, Kubernetes (GKE preferred)
Serverless architectures
Infrastructure-as-code (Terraform preferred)
Data & Vector Database Skills
Hands-on experience with vector stores:
Pinecone, FAISS, Chroma, Weaviate
Data pipeline development for AI applications
Experience handling large-scale enterprise data
 Experience building enterprise GenAI platforms or internal developer platforms
 Exposure to multi-modal AI (text, images, audio)
 Knowledge of:
AI governance, compliance, and security
 Experience in BFSI or regulated industries (good to have)
Role descriptions / Expectations from the Role
1
Vertex AI & GenAI Platform Development (Core Focus)
Design, build, and manage GenAI platforms leveraging Google Vertex AI
Develop reusable platform components and services for:
LLM orchestration
Prompt management
RAG pipelines
Enable scalable deployment of LLM-powered applications across teams
Build internal frameworks, APIs, and SDKs for AI use cases
GenAI Application Development
Develop AI applications using:
LangChain, LangGraph
RAG (Retrieval-Augmented Generation) pipelines
Build use cases such as:
AI copilots
Conversational agents
Document intelligence systems
Integrate models via:
Vertex AI (Gemini models)
OpenAI APIs / Azure OpenAI
AWS Bedrock
2
Python Development (Core Requirement)
Build scalable backend services using Python
Use frameworks such as:
FastAPI / Flask
Develop orchestration layers for multi-step GenAI workflows (LangGraph)
Write clean, modular, and reusable code for AI systems

Work arrangement
No