POSITION DESCRIPTION
We are looking for an AI Specialist with hands-on experience building and deploying production AI applications using Azure OpenAI Services and the OpenAI ecosystem. The ideal candidate has deep expertise in generative AI, large language models (LLMs), multi-agent architectures, and conversational AI — with a strong background in Python backend development and cloud-based architecture on Microsoft Azure. You will be responsible for designing, developing, and scaling AI-driven applications that leverage Azure OpenAI and OpenAI APIs to solve complex business problems in a real-world, customer-facing production environment.
ESSENTIAL DUTIES AND TASKS
- Design and implement AI-powered agents using OpenAI models (GPT-4o, GPT-real time-audio, etc.) and the OpenAI Agents SDK, including multi-agent orchestration with handoff patterns.
- Develop and maintain a multi-agent system with specialized agents that collaborate through a state-machine-driven booking workflow.
- Build production-grade prompt engineering systems — versioned, modular prompts with step-by-step agent instructions, tool references, and cross-agent handoff logic.
- Develop secure and scalable REST APIs using FastAPI (Python), including streaming responses (SSE), WebSocket &WebRTC handlers, and middleware for session validation and rate limiting.
- Implement AI safety and guardrails — input/output guardrails for PII detection, jailbreak prevention, discount policy enforcement, and voucher compliance using pattern-matching and LLM-based approaches.
- Build and maintain the frontend using TypeScript — supporting both text chat and voice chat interfaces.
- Design and manage database layers — MongoDB, Redis, and SQL Server.
- Implement LLM observability using Datadog, Azure Application Insights.
- Build and maintain CI/CD pipelines using Azure DevOps — PR pipelines, CD pipelines, QA and Production deployment pipelines with automated unit testing, code quality checks, and LLM evaluation stages.
- Collaborate with cloud architects, QA, and product stakeholders to translate business requirements into AI-driven experiences.
- Provide technical mentoring and code review guidance to team members, maintaining comprehensive documentation and coding standards.
FESSIONAL SKILLSET QUALIFICATIONS
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.•
- 5+ years of experience in AI/ML engineering, with 2+ years focused on Gen-AI (Azure OpenAI, OpenAI APIs) or similar LLM platforms.
- Strong programming skills in Python with type annotations, and experience with FastAPI, Pydantic, async/await patterns, and modern Python tooling (UV, Ruff, MyPy).
- Expertise in Microsoft Azure — Azure OpenAI, Azure Identity, Azure Redis Cache, Azure DevOps Pipelines.
- Hands-on experience with the OpenAI Agents SDK or similar agent frameworks — multi-agent orchestration, tool calling, function tools, agent handoffs, and guardrails.
- Production experience building conversational AI / chatbot applications with real-world usage in NLP, booking flows, or customer-facing domains.
- Experience with MongoDB, Redis, and SQL Server for database operations in production applications.
- Experience building and deploying containerized applications using Docker and Docker Compose.
- Deep understanding of AI safety and responsible AI — input/output guardrails, PII detection/redaction, jail break prevention, and policy compliance enforcement.
- Strong experience with prompt engineering — versioned prompts, multi-step instructions, few-shot examples, tool description optimization, and cross-agent prompt coordination.
- Experience with LLM observability and monitoring — Datadog, tracing, span creation, token usage tracking, and structured logging.
- Strong analytical, problem-solving, and debugging skills with a focus on code quality, test coverage, and production reliability.
PREFERRED QUALIFICATIONS
- Microsoft certifications (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert).
- Experience with MLOps — model evaluation pipelines, LLM evaluation frameworks, experiment tracking.
- Experience with OpenAI Realtime API — WebRTC-based voice interactions, real-time speech-to-text and text-to-speech.
- Knowledge of Azure Kubernetes Service (AKS), Azure Functions, or serverless deployment patterns.
- Experience with pre-commit hooks, code quality automation (Ruff, MyPy, ESLint, Prettier), and Git-based workflow enforcement.
- Familiarity with Agile/Scrum methodologies and Azure DevOps Boards for project management.
- Contributions to open-source AI/ML projects or technical blogs is a bonus.