AI Solutions Engineer *Global

AI Solutions Engineer 

MGT Consulting · India (Remote) · Full-time

MGT is a US-based management consulting firm serving public sector and education agencies, alongside clients in technology, finance, and advisory. With several decades of experience and significant recent growth, MGT has built a dedicated AI Operating Group (AI OG) — focused on designing, building, and deploying AI-powered solutions across the firm and its clients.

The India team is a fully integrated global delivery function, working in close collaboration with US-based consultants and product leads. This is a core engineering role embedded in an active, fast-moving AI practice

The Role

You will design and deliver production-ready, scalable agent-based systems that integrate with Azure cloud services and Microsoft platforms — working directly on AI OG initiatives spanning internal automation, client-facing AI tools, and agentic workflow platforms.

The expectation is strong engineering discipline, end-to-end ownership, and the ability to think in systems. You will build things that get used.

Key Responsibilities

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  Designing and building scalable agentic systems using modern orchestration patterns

  
  


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  Developing multi-agent workflows with tool use, memory, and decision logic

  
  


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  Building backend services and APIs supporting AI-driven applications

  
  


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  Integrating AI systems with enterprise data, platforms, and business workflows

  
  


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  Deploying, scaling, and monitoring applications on Azure-native services

  
  


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  Solving real problems with end-to-end ownership

  
  


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  Partnering with consulting leads to translate ambiguous use cases into working systems

  
  


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  Contributing to internal frameworks, reusable components, and engineering standards

  
  

Core Requirements

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  3+ years of professional backend engineering experience

  
  


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  Strong hands-on experience with Microsoft Azure (compute, storage, networking, security)

  
  


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  Proficiency in Python, C#, or TypeScript

  
  


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  Experience with cloud-native architectures — APIs, messaging, async workflows, identity

  
  


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  Solid understanding of distributed systems and reliability principles

  
  


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  Experience in modern DevOps environments with CI/CD pipelines

  
  


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  Comfortable operating with ambiguity and driving solutions forward independently

  
  

Preferred / AI-Focused Experience

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  Hands-on experience building AI agents, automation systems, or LLM-based applications

  
  


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  Familiarity with orchestration frameworks such as Semantic Kernel, LangGraph, AutoGen etc.

  
  


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  Experience with Azure AI Foundry, Azure OpenAI, or AI Studio

  
  


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  Understanding of RAG architectures, prompt design, and tool calling patterns

  
  


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  Exposure to Copilot Studio, Microsoft Graph, or enterprise SDK integrations

  
  

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Ideal Mindset

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  Builders who ship — not just experiment

  
  


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  Strong ownership and accountability for outcomes

  
  


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  Ability to think in systems, not just in code

  
  


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  Pragmatic about AI capabilities and trade-offs

  
  


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  Cares about maintainability and long-term code health

  
  


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  Collaborative across time zones and disciplines