Role Overview
We are seeking an experienced GenAI / Cloud / Terraform Engineer to design, develop, and deploy enterprise-grade AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and cloud-native technologies. The ideal candidate will have strong expertise in Generative AI, cloud platforms (Azure preferred), Infrastructure as Code (Terraform), and agent orchestration frameworks to build scalable, secure, and reusable AI capabilities.
Responsibilities
- Design, develop, and deploy enterprise AI/ML solutions using approved AI technologies and cloud platforms.
- Build reusable AI capabilities, including copilots, AI agents, APIs, plugins, and domain-specific automation components.
- Develop and operationalize AI-powered applications such as coding assistants, recommendation engines, enterprise search assistants, and workflow automation solutions.
- Design and implement Retrieval-Augmented Generation (RAG) solutions for text-to-code, diagram-to-code, knowledge retrieval, recommendation systems, and enterprise automation.
- Develop AI-powered search solutions, chatbots, and REST APIs to improve business productivity and user experience.
- Design and implement AI agent-based systems featuring:
- Tool invocation and function calling
- Multi-step reasoning workflows
- Autonomous task execution
- Develop scalable AI solutions using OpenAI, LLMs, vector databases, embeddings, and indexing techniques.
- Build and deploy AI workloads on cloud platforms, preferably Azure (AWS experience is also acceptable).
- Develop and maintain MCP Servers for seamless integration with AI agents (e.g., Copilot Agent Mode).
- Create reusable Terraform modules and Infrastructure as Code (IaC) frameworks for AI infrastructure.
- Ensure secure coding standards, monitoring, logging, and operational excellence across AI applications.
Requirements
Experience Required
- Total IT Experience: 6+ Years
- Generative AI: 3+ Years
- Cloud Platforms (Azure/AWS/GCP): 5+ Years
- Terraform: 2+ Years
Required Skills
- Generative AI: Strong expertise in Large Language Models (LLMs), OpenAI, Retrieval-Augmented Generation (RAG), AI Agents.
- Experience building enterprise AI skills such as copilots, agents, APIs, reusable services, and plugins.
- Hands-on experience with vector databases and semantic search implementations.
- Experience with AI evaluation frameworks such as: RAGAS, DeepEval.
- Experience implementing model fine-tuning techniques including: LoRA, QLoRA.
- AI Agent Frameworks: Experience with one or more of: LangGraph, AutoGen, CrewAI.
- Programming: Strong proficiency in at least one of: Python, .NET, Node.js.
- Cloud & Infrastructure: Azure (Preferred), AWS (Acceptable), Terraform (Infrastructure as Code).
- AI Integration: MCP Server development, Function Calling, Tool Invocation, Agent Orchestration, API Development.
Preferred Qualifications
- Experience building enterprise AI platforms or reusable AI frameworks.
- Experience creating AI skill catalogs or internal developer platforms.
- Experience creating reusable Terraform frameworks.
- Experience standardizing Infrastructure as Code across enterprise teams.
- Strong understanding of secure coding practices.
- Experience with monitoring and observability tools such as Splunk.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Nice to Have
- Azure OpenAI Services
- Azure AI Foundry
- Azure AI Search
- Kubernetes (AKS/EKS)
- Docker
- CI/CD Pipelines
- GitHub Actions or Azure DevOps
- Prompt Engineering
- Model Evaluation & Guardrails