About the role
Responsibilities:
- Design, develop, and deploy end-to-end Generative AI solutions for enterprise use cases.
- Architect and implement Retrieval-Augmented Generation (RAG) pipelines.
- Lead complete GenAI POC development, including solution architecture, development, testing, and deployment.
- Design and optimise prompt engineering strategies for improved LLM performance.
- Develop and orchestrate Large Language Model (LLM) workflows and agent-based AI systems.
- Build scalable backend services and APIs using Python, FastAPI, or Flask.
- Integrate GenAI applications with enterprise platforms, databases, and business systems.
- Deploy and manage applications on Microsoft Azure, including Web Apps, Function Apps, and Virtual Machines.
- Work with Databricks for data engineering pipelines, model workflows, and AI solution integration.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver AI-driven solutions.
- Mentor junior developers and provide technical leadership throughout the project lifecycle.
Requirements:
- 4+ years of overall software development experience.
- Hands-on experience delivering production-level Generative AI solutions (POCs or personal projects alone will not be considered).
- Strong expertise in: Retrieval-Augmented Generation (RAG), Prompt Engineering, LLM workflows and orchestration, Enterprise GenAI solution development.
- Strong programming skills in Python.
- Experience building REST APIs using FastAPI, Flask, or similar frameworks.
- Proven ability to build complete GenAI solutions from scratch.