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
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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.
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.
Required Skills 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 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) 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 Vector Databases
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pgvector
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Pinecone
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Weaviate Cloud & Platforms
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AWS (Bedrock, ECS Fargate, S3, Guardrails) Databases
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PostgreSQL
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DynamoDB Security & Identity
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Ping Identity
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OAuth2 / OIDC
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SSO, Authentication & Authorization 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 Frontend
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ReactJS
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Streamlit Enterprise Tools
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Portkey (AI Gateway)
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Apigee (API Gateway)
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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.
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Familiarity with LLMOps and AI observability platforms. ________________________________________ What We're Looking For
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Strong full stack engineering mindset with GenAI expertise.
- 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. ________________________________________ Experience
- 10+ years of software engineering experience
- 3+ years hands-on experience delivering GenAI-based enterprise applications
