Job Description

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

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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.

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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.

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Experience

• 10+ years of software engineering experience

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

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