Senior AI Developer – Agentic AI / Conversational AI 7Yeras (Contract Opportunity)

Job Type: Full-Time / Contract

Experience Level: 7 to 10+ Years (Overall), with robust hands-on experience in AI/LLM application development.

Role Overview

We are seeking a hands-on, highly motivated Senior AI Developer specializing in Conversational AI and Agentic AI solutions.

In this high-impact role, you will design, develop, and scale production-ready AI applications, build intelligent autonomous agents, and orchestrate complex LLM-driven workflows.

You will bridge the gap between architectural vision and hands-on technical execution—integrating enterprise backend systems, ensuring robust observability, and implementing security, privacy, and reliability best practices across our AI ecosystem.

Key Responsibilities

• AI Agent & Workflow Development: Design and build advanced Conversational AI and Agentic AI applications using Large Language Models (LLMs) and modern orchestration frameworks.
• Agent Architecture: Implement core agentic patterns, including state management, intent routing, tool calling, multi-agent workflow orchestration, and sophisticated fallback mechanisms.
• Backend & API Integration: Develop scalable backend services and APIs (using Python/FastAPI) to seamlessly connect AI capabilities with enterprise systems and third-party tools.
• Orchestration & Tooling: Build and integrate agent tools using REST APIs, function calling, Model Context Protocol (MCP), and structured contracts primarily utilizing frameworks like LangGraph and LangChain.
• Knowledge Retrieval (RAG): Design and deploy Retrieval-Augmented Generation (RAG) architectures, embeddings, vector search, and knowledge retrieval pipelines.
• Observability & Monitoring: Implement end-to-end LLM observability covering tracing, latency, token consumption, cost optimization, error tracking, and response quality.
• Evaluation & Quality Assurance: Create evaluation and automated testing pipelines to continuously monitor, tune, and improve AI accuracy, consistency, and reliability.
• Responsible AI & Security: Ensure compliance with enterprise security, data privacy, auditability, and responsible AI guardrails.
• Cross-functional Collaboration: Partner closely with architecture, frontend, backend, cloud, SRE, QA, and product teams to drive technical designs, code reviews, and production troubleshooting.

Required Skills & Technical Qualifications

• Core Programming: Strong hands-on software development experience in Python, including robust backend and API development using FastAPI or equivalent frameworks.
• LLM & AI Expertise: Hands-on commercial experience developing production-grade LLM-based and Conversational AI applications.
• Orchestration Frameworks: Practical experience utilizing LangGraph, LangChain, or equivalent agent orchestration tools.
• Agentic Concepts: Deep understanding of state management, intent routing, tool calling, workflow orchestration, and exception handling in AI agents.
• Cloud Platforms: Hands-on experience with Azure OpenAI, Azure AI Foundry (Microsoft Foundry), or equivalent cloud-hosted LLM enterprise ecosystems.
• Integration Skills: Proven track record of integrating LLM apps with REST APIs, relational/vector databases, and core enterprise systems.
• Advanced LLM Techniques: Mastery of prompt engineering, function calling, structured outputs, and response-handling patterns.
• Observability & RAG: Familiarity with LLM monitoring/tracing tools, embeddings, vector search, and RAG design patterns, alongside core AI security and data privacy fundamentals.
• Soft Skills: Exceptional problem-solving, analytical, and communication skills with the ability to articulate complex technical concepts clearly.

Nice-to-Have Qualifications

• Experience implementing MCP (Model Context Protocol) servers/clients or MCP-based integrations.
• Experience with Azure AI Search and specialized vector databases.
• Familiarity with LLM observability platforms such as LangSmith, Langfuse, OpenTelemetry, Azure Monitor, or Application Insights.
• Experience with automated LLM evaluation frameworks and quality testing suites.
• Deployment experience on Azure using Docker, containers, and managed cloud services, alongside CI/CD pipelines (GitHub Actions).
• Background in building enterprise portals, customer-facing applications, contact centers, CRM systems, or deterministic/controlled AI workflows.