Python Developer (Genai)

Senior Full Stack GenAI Engineer with 10+ years of experience to design and build agentic AI solutions that automate enterprise workloads and business processes.

The ideal candidate will have strong expertise in Python-based backend development, LLM-powered applications, cloud-native deployment, vector databases, and modern DevOps practices. This role involves building end-to-end AI systems that integrate with enterprise platforms, automate workflows, and deliver production-grade AI applications.

Key Responsibilities

- Design and develop agentic AI applications that automate enterprise workflows and decision-making processes.

- Build scalable backend services using Python, FastAPI, and Pydantic.

- Develop and deploy LLM-powered applications using models such as GPT and Claude.

- Build AI agents and orchestration workflows using LangChain or Strands.

- Implement Retrieval Augmented Generation (RAG) solutions using vector databases (pgvector, Pinecone, Weaviate).

- Perform data analysis, preparation, and curation to build high-quality datasets for AI and knowledge retrieval systems.

- Design and implement document ingestion pipelines for enterprise knowledge sources such as SharePoint, Confluence, and Jira.

- Deploy AI workloads on AWS (Bedrock, ECS Fargate, S3) with proper security and scalability practices.

- Develop and integrate enterprise APIs using REST, GraphQL, WebSockets, and web services.

- Implement secure authentication and authorization using Ping Identity, OAuth2, OIDC, and SSO.

- Build user interfaces for AI applications using ReactJS or Streamlit.

DevOps & Deployment

- Build and manage CI/CD pipelines using Jenkins or GitLab.

- Implement GitOps practices for automated deployments.

- Containerize applications using Docker and deploy to cloud platforms.

- Implement security best practices, vulnerability scanning, dependency management, and container security.

Required Skills

Backend & APIs

- Python

- FastAPI

- Pydantic

- REST APIs, GraphQL, WebSockets

GenAI & Agent Frameworks

- LLMs (GPT, Claude)

- LangChain or Strands

- Retrieval Augmented Generation (RAG)

- NLP (Natural Language Processing)

Data & AI Pipelines

- Data analysis, data preparation, and data curation

- Document ingestion and knowledge base creation

- Embeddings and semantic search

Vector Databases

- pgvector

- Pinecone

- Weaviate

Cloud & Platforms

- AWS (Bedrock, ECS Fargate, S3, Guardrails)

Databases

- PostgreSQL

- DynamoDB

Security & Identity

- Ping Identity

- OAuth2 / OIDC

- SSO, Authentication & Authorization

DevOps

- Jenkins

- GitLab

- GitOps practices

- Docker containerization

- Security vulnerability mitigation

Frontend

- ReactJS

- Streamlit

Enterprise Tools

- Portkey (AI Gateway)

- Apigee (API Gateway)

- Jira, Confluence, SharePoint

Preferred Qualifications

- Experience building AI agents for enterprise automation.

- Experience implementing AI guardrails and LLM governance frameworks.

- Experience building enterprise copilots or knowledge assistants.

- Familiarity with LLMOps and AI observability platforms.

What We're Looking For

- Strong full stack engineering mindset with GenAI expertise.

- Experience building production-grade AI systems.

- Ability to work across AI, backend, cloud, and DevOps stacks.

- Passion for building automation solutions powered by agentic AI.

Experience

- 10+ years of software engineering experience

- 3+ years hands-on experience delivering GenAI-based enterprise applications