Requirements

Expected technologies

AI

FastAPI

Python

Langchain

Langgraph

CrewAI

Microsoft Azure

Pandas

.NET

RAG

Our requirements

• Programming Proficiency: Python (FastAPI), RAG (Retrieval Augmented Generation), Prompt Engineering, Vector Database and Embedding models
• Frameworks: LangChain, LangGraph, LlamaIndex etc.
• Multi-Agent libraries/frameworks: CrewAI, Autogen, Taskweave etc.
• Azure Functions
• Data Processing: Expertise in data manipulation using Pandas, NumPy
• Cloud Computing: Azure (current focus right now and a must have). Familiarity with cloud platforms, such as Azure and their relevant AI services
• Familiarity with data engineering concepts, including data pipelines, data integration, and data warehousing. Ability to work with large datasets and perform data cleaning, transformation, and manipulation
• Soft Skills: Analytical thinking, problem-solving, effective communication. Strong analytical and creative problem-solving skills. Experience working within a fast-paced
• Agile development environment
• Hands-on development experience with .NET technology stack, preferred: C#, SQL Server, Azure PaaS, Azure DevOps and CI/CD Pipelines (including YAML)

Your responsibilities

• Independently executes and delivers new capabilities with high-quality based on documented requirements
• Actively participate in both technical and functional discussions relative to ongoing and future user story development
• Provide input to the development of project initiation documents including objectives, scope, approach and deliverables, when needed
• Communicate implications of development decisions, issues and plans
• Establish strong working relationships with the development team, business, operations and other IT team members
• Participate in and support cross-team process improvement initiatives
• Assist in the creation and maintenance of application guidelines, standards, policies and procedures and disseminate to IT teams
• Ensure documentation is captured in a knowledge repository; publicize deliverable location to the organization as necessary
• Collaborates with technology owners and researches industry trends to assist project development and operational support activities
• Data Handling: Collect, preprocess, and analyze large datasets for training models
• Deploy AI Solutions: Integrate AI models into existing systems or develop new applications
• Collaborate with Teams: Work with data scientists and other stakeholders to understand project needs