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.
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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.
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Key Responsibilities
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• Design and develop agentic AI applications that automate enterprise workflows and decision-making processes.
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• Build scalable backend services using Python, FastAPI, and Pydantic.
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• Develop and deploy LLM-powered applications using models such as GPT and Claude.
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• Build AI agents and orchestration workflows using LangChain or Strands.
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• Implement Retrieval Augmented Generation (RAG) solutions using vector databases (pgvector, Pinecone, Weaviate).
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• Perform data analysis, preparation, and curation to build high-quality datasets for AI and knowledge retrieval systems.
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• Design and implement document ingestion pipelines for enterprise knowledge sources such as SharePoint, Confluence, and Jira.
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• Deploy AI workloads on AWS (Bedrock, ECS Fargate, S3) with proper security and scalability practices.
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• Develop and integrate enterprise APIs using REST, GraphQL, WebSockets, and web services.
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• Implement secure authentication and authorization using Ping Identity, OAuth2, OIDC, and SSO.
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• Build user interfaces for AI applications using ReactJS or Streamlit.
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DevOps & Deployment
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• Build and manage CI/CD pipelines using Jenkins or GitLab.
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• Implement GitOps practices for automated deployments.
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• Containerize applications using Docker and deploy to cloud platforms.
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• Implement security best practices, vulnerability scanning, dependency management, and container security.
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Required Skills
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Backend & APIs
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• Python
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• FastAPI
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• Pydantic
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• REST APIs, GraphQL, WebSockets
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GenAI & Agent Frameworks
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• LLMs (GPT, Claude)
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• LangChain or Strands
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• Retrieval Augmented Generation (RAG)
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• NLP (Natural Language Processing)
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Data & AI Pipelines
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• Data analysis, data preparation, and data curation
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• Document ingestion and knowledge base creation
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• Embeddings and semantic search
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Vector Databases
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• pgvector
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• Pinecone
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• Weaviate
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Cloud & Platforms
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• AWS (Bedrock, ECS Fargate, S3, Guardrails)
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Databases
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• PostgreSQL
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• DynamoDB
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Security & Identity
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• Ping Identity
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• OAuth2 / OIDC
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• SSO, Authentication & Authorization
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DevOps
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• Jenkins
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• GitLab
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• GitOps practices
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• Docker containerization
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• Security vulnerability mitigation
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Frontend
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• ReactJS
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• Streamlit
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Enterprise Tools
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• Portkey (AI Gateway)
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• Apigee (API Gateway)
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• Jira, Confluence, SharePoint
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Preferred Qualifications
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• Experience building AI agents for enterprise automation.
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• Experience implementing AI guardrails and LLM governance frameworks.
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• Experience building enterprise copilots or knowledge assistants.
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• Familiarity with LLMOps and AI observability platforms.
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What We're Looking For
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• Strong full stack engineering mindset with GenAI expertise.
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• Experience building production-grade AI systems.
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• Ability to work across AI, backend, cloud, and DevOps stacks.
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• Passion for building automation solutions powered by agentic AI.
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Experience
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• 10+ years of software engineering experience
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• 3+ years hands-on experience delivering GenAI-based enterprise applications