Senior AI Engineer [T500-27959]

Talent500 is hiring for one of its clients.

About Itineris:

Itineris is a leading technology company that specializes in innovative SaaS solutions for water and energy utilities. Its flagship solution, UMAX, is a highly configurable Customer Information System (CIS) and CRM platform built on Microsoft Dynamics 365. UMAX enables utilities to streamline a wide range of operations – including customer service, field services, billing, asset management, and data analytics. Today, Itineris supports over 30 prominent utility providers across 7 countries and 11 U.S. states, serving more than 8 million customer accounts.

AI Engineer

Role Overview:

We are seeking a motivated and talented AI Engineer to join our growing AI Practice team in Hyderabad. In this role, you will design, build, and operate AI-powered applications — from initial architecture through to production deployment on Azure — and you will also own a meaningful part of how we experiment on and evaluate the LLM agents and systems we ship, including UMAX’s agent harness, the orchestration layer that powers UMAX’s agentic capabilities.

This is fundamentally a hands-on engineering role: you write production-grade code, own deployments, and care about what happens after the merge. At the same time, your instinct for rigorous evaluation and systematic experimentation — forming hypotheses, running structured tests on prompt strategies and orchestration patterns, and measuring whether a change is actually an improvement — is just as central to the job. As you grow with the team, you may naturally lean more into one side of this or the other, but on day one this role expects range across both.

Key Responsibilities:

• AI Application & Agent Development Design and build AI-powered applications with agentic orchestration, RAG pipelines, and LLM integrations at their core. Own prompt and system prompt architecture, tool/function definitions, context management, and orchestration flow design, translating requirements into well-architected, maintainable solutions that work reliably in production.
• Evaluation & Experimentation Design evaluation frameworks for agent output quality — scoring rubrics, automated test suites, regression tracking — and run structured experiments across prompt strategies, tool configurations, and orchestration patterns. Form clear hypotheses, measure outcomes, and translate results into concrete improvements.
• Azure Engineering & Deployment Own the Azure infrastructure and deployment pipelines for AI workloads. This includes containerized and serverless deployments, IaC with Bicep, and keeping environments consistent across dev, staging, and production.
• CI/CD Build and maintain robust CI/CD pipelines for AI applications using Azure DevOps. Integrate security scanning, dependency management, and automated testing into the delivery pipeline as first-class concerns, not afterthoughts.
• Platform Operations Monitor, debug, and improve AI applications in production. Take ownership when things go wrong and drive incidents to resolution.
• LLM & Agentic Landscape Research Stay close to developments in the LLM and agentic AI space — new models, orchestration frameworks, evaluation techniques — and evaluate their relevance to UMAX’s architecture, bringing in what matters.
• Engineering Standards & Collaboration Write clean, well-tested, reviewable code and participate actively in code reviews. Document experiment findings and design decisions clearly, and collaborate with peers across the AI Practice team to help raise the engineering bar. Leverage AI for engineering through GitHub Copilot, Claude Code, or similar, and actively expand our AI-first development workflow.

Required Skills & Qualifications:

• Software Engineering:
• Strong proficiency in Python or C#
• Solid understanding of software design principles: modularity, testability, observability
• Experience building and consuming RESTful APIs and microservices architectures
• Comfortable working across the full development lifecycle

AI & LLM Engineering:

• Deep practical understanding of LLM behavior: prompting, context windows, tool/function calling, retrieval-augmented generation, multi-step reasoning
• Hands-on experience with agentic orchestration frameworks (LangChain, Semantic Kernel, AutoGen, or similar)
• Familiarity with Azure AI Foundry and Cognitive Services ecosystem
• Experience wit…