Senior Fullstack/ GenAI developer

JOB DESCRIPTION: GEN AI DEVELOPER / AGENTIC AI ENGINEER

Job Overview We are looking for a Gen AI Developer / Agentic AI Engineer with 5 years of professional software engineering experience to design, build, and scale Generative AI and Agentic AI solutions for internal platforms, reusable accelerators, and enterprise client engagements. This role bridges hands-on software development with LLMs, RAG, multi-agent workflows, and secure backend infrastructure.

Role Overview & Key Responsibilities

Core Responsibilities

● Backend & System Integration: Develop robust Python microservices, RESTful APIs, WebSockets, and asynchronous data pipelines to ensure reliable communication between AI components and enterprise software.

● Full-Stack Application Development: Create scalable, end-to-end web applications and interfaces using modern backend and frontend stacks (e.g., Python, Java, JavaScript, Django, or MERN).

● Architecture & Framework Selection: Evaluate technical requirements to select the optimal approach per use case, including classic LLM workflows, single/multi-agent architectures, or hybrid setups.

● Platform Accelerators & Reusable Tooling: Architect reusable platform components, including custom API connectors, orchestration modules, prompt libraries, evaluation suites, and output guardrails.

● Gen AI & Agentic AI Engineering: Design, develop, and deploy production-ready Generative AI systems.

● RAG & Knowledge Retrieval Systems: Build and optimize advanced Retrieval-Augmented Generation (RAG) pipelines.

● Responsible AI & Security Operations: Enforce strict data privacy protocols, network access controls, prompt-injection mitigations, and service-level authentication to ensure enterprise security and compliance.

● Agile Engineering & Delivery: Collaborate within cross-functional Scrum teams using Git and automated CI/CD pipelines to rapidly deliver PoCs, MVPs, and production-ready systems.

Role Requirements & Candidate Profile

Must-Have Qualifications

● Experience Level: 5 years of professional software engineering experience building and deploying production-grade systems.

● Gen AI Core: Practical experience with Large Language Models (LLMs), prompt engineering, RAG architectures, and vector databases .

● Agentic Frameworks: Hands-on experience developing with the agentic framework ecosystem (e.g., LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel). ● Backend Development: Demonstrated expertise in building scalable REST APIs and microservices using backend frameworks such as FastAPI, Django, or Flask. ● DevOps & Infrastructure: Experience with Docker containerization, Linux environments, Git version control, and CI/CD pipelines.

● Security & Integration: Working knowledge of API authentication/authorization protocols, network control, and secure coding practices.

Nice-to-Have Qualifications

● Advanced Knowledge Retrieval: Practical exposure to GraphRAG, Knowledge Graphs, or complex enterprise metadata pipelines.

● AI Observability & Guardrails: Experience with agent tracing, prompt evaluation frameworks, and LLM monitoring tools (e.g., LangSmith, Langfuse, or Guardrails AI). ● Cloud & Serverless Architecture: Hands-on deployment experience across cloud platforms (AWS, Azure, or GCP).

● Developer Tooling: Track record of building developer productivity tools, enterprise copilots, or reusable platform accelerators.