Role Overview

We are looking for an experienced Applied AI / Agentic Solutions Engineer to design, prototype and deliver enterprise AI solutions using the Microsoft AI ecosystem.

This role sits between architecture, engineering and business/domain expertise. You will work with architects, .NET engineers and functional experts to turn complex business processes into grounded, explainable and production-ready agentic solutions.

A key initial focus will be creating AI capabilities that can ingest authoritative information, compare it with existing business configurations, identify changes or gaps, provide supporting evidence, route recommendations for human approval, and validate changes before production.

We need someone who is hands-on and outcome-driven, able to move from problem definition to working prototype quickly, then partner with engineering teams to productionise the solution.

Key Focus: Agentic AI & GitHub Copilot

- Design and build specialised AI agents and agentic workflows.
- Create and refine GitHub Copilot custom agents, instructions, prompts and MCP integrations.
- Establish reusable agent patterns, guardrails and evaluation approaches.
- Apply the right combination of AI, deterministic automation and human judgement.
- Rapidly prototype solutions and prove value before wider engineering implementation.

Key Responsibilities

- Design and prototype AI/agentic solutions using Azure AI, LLMs, C#/.NET and Python where appropriate.
- Translate business and domain problems into implementable agent workflows, prompts, tools and integrations.
- Build RAG and grounding solutions using Azure AI Search, embeddings, metadata and authoritative source content.
- Design human-in-the-loop flows for review, approval and exception handling.
- Ensure AI recommendations are grounded, traceable and supported by source evidence.
- Develop AI evaluation and regression testing for retrieval, groundedness, business rules and end-to-end outcomes.




- Work with architects and engineers to productionise prototypes securely and at scale.
- Work directly with functional experts to turn domain knowledge and edge cases into agent behaviour and tests.

Required Skills

- Proven hands-on experience designing and building LLM, RAG or agentic AI solutions.
- Robust software engineering foundation with C#/.NET, Python and/or REST APIs, plus Azure experience.
- Hands-on experience with Azure OpenAI/AI Foundry, Azure AI Search, Semantic Kernel or equivalent agent frameworks.
- Strong understanding of prompt engineering, grounding, RAG, embeddings and structured LLM outputs.
- Experience with AI evaluation, hallucination mitigation, evidence/citation and regression testing.
- Ability to translate an ambiguous business problem into a working AI solution.
- Experience designing human-in-the-loop AI workflows.
- Working knowledge of GitHub Copilot custom agents and MCP, or demonstrable experience with equivalent agent frameworks.
- Strong communication skills across architects, engineers and non-technical domain experts. (In English)

Preferred Skills

- Experience creating reusable agent frameworks, standards or libraries.
- Azure Functions, API Management, Azure DevOps and CI/CD.
- AI security, governance and observability.
- Experience in regulated, rules-heavy or configuration-driven environments.
- Experience processing authoritative documents, policies, regulations or complex business content.
- Payroll, tax, HR or country-compliance knowledge is advantageous, but not required.

Experience

- 5+ years in software engineering, AI engineering or technical solution delivery.
- Hands-on experience delivering production AI/LLM solutions.
- Demonstrable experience taking AI use cases from problem → prototype → evaluation → production.
- Experience working across architecture, engineering and business/domain teams.
- Evidence of personally building AI solutions, rather than solely managing or coordinating their delivery.

📌 Applied AI / Agentic Solutions Engineer (India)
🏢 Elgebra
📍 India