Full Stack AI Engineer

Job Description: Full Stack AI Engineer / Agentic Application Engineer

Future Hire | 2–3 Years Experience | Full-Time

Role Summary:

We are looking for a hands-on Full Stack AI Engineer who can independently build AI-enabled internal applications across frontend, backend, API integrations, and agentic workflows. The resource should be strong in Python/FastAPI and frontend development, with practical exposure to LLM APIs, RAG/agent workflows, and integration-heavy enterprise applications.

Key Responsibilities:

• Design and develop full-stack AI applications covering backend APIs, frontend screens, workflows, and integrations.

• Build and maintain Python/FastAPI-based services for AI automation use cases.

• Develop React/JavaScript-based frontend components and connect them cleanly with backend APIs.

• Implement agentic workflows using tool-calling, orchestration, memory/state handling, and controlled execution patterns.

• Build RAG or retrieval-based modules where required.

• Integrate internal/external APIs, databases, and automation services securely and reliably.

• Write modular, readable, maintainable code with testing discipline.

• Coordinate with DevOps/platform teams for CI/CD and releases.

• Document architecture, APIs, configuration, assumptions, and deployment requirements.

• Work closely with stakeholders to convert requirements into solutions.

Mandatory Skills / Experience:

• 2–3 years hands-on software engineering experience.

• Strong Python programming fundamentals.

• Practical experience with FastAPI.

• Frontend development using React and/or JavaScript/HTML/CSS.

• Database fundamentals: SQL/PostgreSQL/MySQL and/or MongoDB.

• Git/GitHub experience.

• REST API design and debugging.

• Understanding of LLM API integration and prompt/tool workflows.

Preferred / Nice-to-Have Skills:

• LangGraph, CrewAI, Semantic Kernel, LangChain.

• MCP/tool-calling concepts and agent frameworks.

• RAG implementation experience.

• Docker basics.

• AWS/GCP familiarity.

• Enterprise integrations and automation tools.

• Postman, pytest, API/frontend testing.

• Banking/financial services exposure.

KPIs / Success Measures

• Deliver complete frontend-backend AI modules.

• Build reliable FastAPI services.

• Produce reusable components.

• Maintain readable code and documentation.

• Meet sprint commitments and timelines.