Job Description

Mandatory Skills: Advanced GenAI & Agentic Framework Concepts, Cloud Application Integration & Deployment, AI Agents & Tool Calling, Azure AI Foundry, Agentic AI Systems, LangChain, LangGraph

Additional Skills: GitHub

Key Responsibilities:

- Develop and implement Generative AI solutions using platforms such as Amazon Bedrock, Azure OpenAI Service, Azure AI Foundry, Grog, or AI Search Index services.
- Build Retrieval-Augmented Generation (RAG), Graph RAG, or Agentic AI solutions to support enterprise knowledge retrieval and intelligent automation use cases.
- Develop AI-powered applications leveraging Large Language Models (LLMs) aligned with business requirements.
- Develop secure AI services using Python and FastAPI, implement authentication, authorization, asynchronous APIs, request throttling, scheduling, multithreading, and scalable API design where applicable.
- Configure and implement AI agents, tool-calling mechanisms, and intelligent workflow automation solutions.
- Develop and maintain workflows using LangChain or LangGraph to orchestrate AI interactions and business processes.
- Implement prompt engineering, context management, and retrieval strategies to improve AI response quality and relevance.
- Support implementation of vector databases, semantic search, and prompt engineering techniques to improve retrieval quality and AI response accuracy where applicable.
- Support fine-tuning and model customization activities to enhance model performance for domain-specific use cases.
- Integrate AI applications with enterprise systems, databases, external APIs, cloud services, and Model Context Protocol (MCP)-based services where applicable to enable secure, scalable,



and seamless business workflows.
- Perform testing, validation, and evaluation of AI-generated outputs to ensure quality, accuracy, and reliability.
- Monitor AI solution performance and support troubleshooting and optimization activities.
- Maintain technical documentation, prompt configurations, workflow definitions, and implementation artifacts.
- Collaborate with various teams and stakeholders to support successful AI solution delivery.
- Ensure AI solutions are reliable, scalable, maintainable, and aligned with business requirements.

Behavioral Competencies:

- Demonstrates ownership and accountability while delivering high-quality AI solutions.
- Collaborate effectively with various teams and business stakeholders to ensure smooth delivery.
- Maintains a quality-first mindset while developing reliable and effective AI-powered applications.
- Applies strong analytical and problem-solving skills to resolve AI, retrieval, and workflow-related challenges.
- Shows adaptability and willingness to learn evolving AI technologies, frameworks, and industry trends.
- Communicates clearly by sharing progress, risks, assumptions, and dependencies proactively.
- Maintains attention to detail during AI solution development, testing, validation, and deployment activities.
- Works effectively in energetic environments with changing priorities and evolving business requirements.
- Takes initiative in improving AI solution quality, automation effectiveness, and operational efficiency.
- Demonstrates a customer-centric mindset by delivering reliable, high-quality solutions.Role & responsibilities

Preferred candidate profile

Perks and benefits

📌 Full Stack AI Engineer (Bengaluru)
🏢 Fortunefootprints Consulting
📍 Bengaluru