AI Solutions Engineer *Global
MGT
- Location
- Remote (United States)
- Employment
- Full-time
- Level
- Mid Level
Posted 2 weeks ago
About the Role
MGT is a US-based management consulting firm with a dedicated AI Operating Group focused on designing and deploying AI solutions. This role is for an AI Solutions Engineer to build production-ready, scalable agent-based AI systems integrated with Azure services.
Skills
Azure Cloud Services
Python
C#
TypeScript
AI Agent Design
Backend Engineering
Distributed Systems
CI/CD Pipelines
RAG Architectures
API Development
Semantic Kernel
LangGraph
AutoGen
Azure OpenAI
Prompt Design
Cloud-Native Architecture
Perks
- Remote OK
Full job details
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