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

• Designing and building scalable agentic systems using modern orchestration patterns

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

• Building backend services and APIs supporting AI-driven applications

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

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

• Solving real problems with end-to-end ownership

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

• Contributing to internal frameworks, reusable components, and engineering standards

Core Requirements

• 3+ years of professional backend engineering experience

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

• Proficiency in Python, C#, or TypeScript

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

• Solid understanding of distributed systems and reliability principles

• Experience in modern DevOps environments with CI/CD pipelines

• Comfortable operating with ambiguity and driving solutions forward independently

Preferred / AI-Focused Experience

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

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

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

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

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

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Ideal Mindset

• Builders who ship — not just experiment

• Strong ownership and accountability for outcomes

• Ability to think in systems, not just in code

• Pragmatic about AI capabilities and trade-offs

• Cares about maintainability and long-term code health

• Collaborative across time zones and disciplines