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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