MS - Sr. Fullstack Engineer - Job3105 at Taller Technologies

, , -

Full Time

Start Date

Immediate

Expiry Date

12 Apr, 26

Salary

0.0

Posted On

13 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

C#, .NET, Python, React, AI Solutions, Microservices, Docker, Azure, RAG Pipelines, LLM Fine-Tuning, Event-Driven Architecture, CI/CD, Infrastructure as Code, Mentoring, JavaScript, SignalR

Industry

IT Services and IT Consulting

Description

MS - Sr. Fullstack Engineer - Job3105 Summary We are seeking a senior full-stack engineer (70% backend / 30% frontend) to lead the design and delivery of enterprise-grade AI copilots and agentic AI systems, with a strong focus on Microsoft Copilot Foundry and Azure-native AI services. This role is central to building production-ready AI solutions, including retrieval-augmented generation (RAG) pipelines, multi-agent workflows where applicable, and AI copilots that connect LLMs to real-world data and enterprise applications. You will work primarily on backend services, microservices, and Azure platform capabilities, while also contributing to frontend development using React. This is an opportunity to shape architecture, mentor engineers, and deliver practical, iterative AI solutions that drive business value. Responsibilities Design and deploy enterprise AI copilots and custom knowledge-base integrations using Microsoft Copilot Foundry. Design and implement agentic or multi-agent AI systems where appropriate, using frameworks such as LangChain, AutoGen, or CrewAI. Build RAG pipelines and integrate vector databases like Pinecone and Weaviate. Implement agent orchestration and inter-agent communication for distributed AI workflows. Develop LLM fine-tuning workflows and optimize prompt engineering for production use. Build backend services with C# /.NET (ASP.NET Core, Entity Framework, SignalR, Minimal APIs) and Python (FastAPI, Django, Flask). Contribute to frontend development using JavaScript and React (approximately 30% of the role). Architect microservices with Docker containerization and event-driven patterns using Azure Service Bus or RabbitMQ. Implement Azure serverless and integration solutions using Azure Functions and Logic Apps. Create ETL/ELT data pipelines with Azure Data Factory for AI data preparation. Implement CI/CD automation and infrastructure as code using Azure DevOps, ARM/Bicep, or Terraform. Monitor and maintain observability using Application Insights and manage Git workflows and branching strategies. Mentor junior engineers and document architecture decisions, trade-offs, and operational procedures. Requirements 5+ years of professional software engineering experience with senior-level full stack responsibilities. Hands-on experience designing and deploying AI solutions using Microsoft Copilot Foundry. Strong backend development skills in C# /.NET and Python, with experience building production-grade services. Solid front-end development experience with JavaScript and React. Experience building RAG pipelines with vector databases such as Pinecone or Weaviate. Experience with LLM fine-tuning and prompt engineering optimization. Experience with microservices architecture and Docker containerization. Experience with event-driven architectures and message queues (Azure Service Bus, RabbitMQ). Proficiency with Azure platform services including Azure OpenAI Service, Azure Functions, Logic Apps, and Azure Data Factory. Practical experience with CI/CD using Azure DevOps, YAML pipelines, and Infrastructure as Code (ARM/Bicep or Terraform). Demonstrated ability to translate complex AI concepts into business terms and document architecture decisions. Strong problem-solving orientation, preference for MVP and iterative delivery, and experience mentoring junior developers. Nice to Have Experience designing or implementing agentic or multi-agent AI systems using frameworks such as LangChain, AutoGen, or CrewAI. Familiarity with Azure Cognitive Services (Computer Vision, Text Analytics, Speech). Experience managing multi-cloud infrastructure with Terraform.

Responsibilities

Design and deploy enterprise AI copilots and custom knowledge-base integrations. Build production-ready AI solutions, including retrieval-augmented generation pipelines and multi-agent workflows.