AI Automation Developer

Role Summary

We are looking for an experienced Senior AI & Full-Stack Automation Engineer to design, build, and deploy high-impact, AI-powered applications and enterprise automation solutions using Microsoft Azure, Full-Stack Web Technologies, and Generative AI.

In this role, you will bridge the gap between user-facing front-end web interfaces, robust back-end APIs, and cutting-edge Retrieval-Augmented Generation (RAG) architecture. You will own the full product lifecycle—from designing intuitive front-end AI interactions and backend orchestration to integrating Azure OpenAI, vector search databases, and cloud-native automation workflows.

Key Responsibilities

1. LLM & RAG Architecture Engineering

• RAG System Design: Architect and deploy enterprise Retrieval-Augmented Generation (RAG) pipelines on Azure, utilizing Azure AI Search (formerly Cognitive Search) or vector databases (pgvector, Pinecone, Qdrant) for hybrid search, semantic ranking, and document chunking.

• Azure OpenAI Integration: Develop and tune generative AI capabilities using Azure OpenAI Service (GPT-4/GPT-4o, embedding models), implementing system prompting, function calling/tooling, and multi-agent coordination frameworks (LangChain, Semantic Kernel, LlamaIndex, or AutoGen).

• LLMOps & Evaluation: Establish continuous evaluation metrics (measuring hallucination, faithfulness, context relevancy), guardrails (Azure AI Content Safety), and token/cost optimization strategies.

2. Back-End Microservices & Automation

• API Development: Design, build, and maintain scalable RESTful and Event-Driven APIs using Python (FastAPI/Flask) or Java, SpringBoot

• Serverless & Workflow Orchestration: Build serverless automation pipelines and data ingestion streams using Azure Functions, Azure Logic Apps, and Event Grid.

• Database Management: Structure relational data models and vector repositories to maintain high performance and low-latency response times.

3. Front-End Development & User Experience

• Interactive AI Interfaces: Build intuitive, responsive front-end user interfaces using React, Next.js, or TypeScript/JavaScript.

• Real-time UX Patterns: Design streaming chat interfaces (Server-Sent Events/WebSockets), document viewer integrations, citation callouts, and human-in-the-loop review dashboards to allow business users to inspect and refine AI outputs.

4. Delivery, Security & Cloud Engineering

• Collaborate with business stakeholders and product leaders to identify manual operational bottlenecks and convert them into automated AI workflows.

• Enforce security, data privacy, and governance standards (Azure RBAC, Key Vault, VNet integration).

• Implement CI/CD automation and infrastructure monitoring using Git, Azure DevOps, and cloud telemetry tools.

Qualifications

Required Experience:

• Overall Experience: 3+ years in full-stack software development, cloud automation, or AI engineering.

• Generative AI & RAG: Hands-on experience building and deploying RAG architectures, semantic retrieval, vector search, and LLM applications using Azure OpenAI or related APIs.

• Back-End Expertise: Proficiency in Python or C# (.NET Core), with strong expertise in API design, microservices, and asynchronous programming.

• Front-End Expertise: Proficiency in modern client-side frameworks (React, Next.js, or TypeScript) to build user-facing web applications.

• Azure Ecosystem: Practical experience with Azure AI Services, Azure AI Search, Azure Functions, Logic Apps, and database systems (Azure SQL, Cosmos DB, or PostgreSQL).

• DevOps: Experience with Git, Docker, CI/CD pipelines, and Azure DevOps or GitHub Actions.

Preferred / Bonus Skills:

• Experience with framework orchestrators like Microsoft Semantic Kernel, LangChain, or AutoGen.

• Familiarity with enterprise data connectors and document parsing libraries (e.g., Unstructured, Azure AI Document Intelligence).

• Microsoft Azure Certifications (e.g., Azure AI Engineer Associate, Azure Developer Associate).

• Knowledge of fine-tuning open-source models or applying agentic workflows in business process automation.