AI Engineer with .Net

Appsierra Group; India; On-site; INR 1,200,000 - 1,600,000; Full time

Job summary

Appsierra Group in India is seeking a senior software engineer to design, develop, and maintain scalable enterprise applications using C#/.NET and ASP.NET Core. You will build RESTful APIs, backend services, and microservices powering AI-enabled applications.

The role requires strong experience with SQL Server, Git, Azure DevOps, CI/CD, and Docker, plus hands-on AI capabilities with Python and LLMs. You will collaborate across teams to deliver high-quality solutions and drive secure, scalable

Qualifications

• 5+ years of professional software development experience.
• Expertise in C#/.NET and ASP.NET Core with enterprise apps.
• Experience designing REST APIs and microservices.
• Strong SQL Server and relational DB skills.
• Experience with Git, Azure DevOps, CI/CD pipelines, and Docker.
• AI-focused experience with Python, LLMs, and RAG is preferred.

Responsibilities

• Design, develop, and maintain scalable enterprise applications using C#/.NET.
• Build RESTful APIs, backend services, and microservices.
• Collaborate with architects, product owners, and cross-functional teams.
• Ensure production-ready software following best practices.
• Integrate internal and third-party platforms into the ecosystem.
• Utilize Azure DevOps for agile delivery, source control, CI/CD, and work management.

Skills

C#/.NET

ASP.NET Core

REST APIs

Microservices

SQL Server

Git

Azure DevOps

CI/CD

Docker

Python

LLMs

RAG

Vector databases

Tools

Git

Azure DevOps

Docker

Kubernetes

Job description

Key Responsibilities

Software Engineering

• Design, develop, and maintain scalable enterprise applications using C#/.NET and ASP.NET Core.
• Build RESTful APIs, backend services, and microservices that power AI-enabled applications.
• Develop clean, maintainable, and production-ready software following engineering best practices.
• Collaborate with architects, product owners, and cross-functional engineering teams to deliver high-quality solutions.
• Engineer reusable components with a strong focus on scalability, reliability, performance, and security.
• Integrate internal and third-party platforms into Epiq's operational ecosystem.
• Utilize Azure DevOps for agile delivery, source control, CI/CD, and work management.

AI Application Development

• Build AI-powered features using Python and modern LLM technologies.
• Develop intelligent agents that automate operational workflows and business processes.
• Design and implement Retrieval-Augmented Generation (RAG) solutions.
• Build and integrate Model Context Protocol (MCP) services and tools.
• Develop multi-agent workflows using modern agentic frameworks.
• Integrate enterprise applications with LLM services through APIs.
• Apply prompt engineering and AI evaluation techniques to improve solution quality.
• Modernize existing operational automations using AI-enabled architectures.

Required Qualifications

• 5+ yearsof professional software development experience.
• Strong hands-on experience developing enterprise applications usingC#/.NET and ASP.NET Core.
• Proficiency in designingREST APIs and microservices.
• Experience with SQL Server or other relational databases.
• Strong understanding of object-oriented programming, software design patterns, and scalable system design.
• Experience with Git, Azure DevOps, CI/CD pipelines, and Docker.

AI Experience

Practical experience building AI-enabled applications using:

• Python
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Vector databases and embeddings
• Prompt engineering
• AI API integrations (OpenAI, Azure OpenAI, Anthropic, Gemini, etc.)

Experience with one or more of the following is preferred:

• Semantic Kernel
• LangGraph
• CrewAI
• AutoGen
• OpenAI Agents SDK

Working knowledge of:

• Model Context Protocol (MCP)
• Agent orchestration
• Tool calling
• AI workflow automation

Preferred Qualifications

• Experience with Microsoft Azure and Azure AI services.
• Azure OpenAI or Azure AI Foundry.
• Kubernetes and containerized deployments.
• Event-driven or distributed architectures.
• Enterprise workflow automation.
• Experience integrating AI capabilities into existing enterprise software products.