AI Engineer [T500-27958]

Talent500; Hyderabad; On-site; INR 2,000,000 - 3,600,000; Full time

Job summary

Itineris is recruiting an AI Engineer to join its Hyderabad-based AI Practice. You will design, build, and operate AI-powered applications with agentic orchestration, integrating RAG pipelines and LLMs at scale on Azure.

You will own experiments, evaluation frameworks, and the orchestration layer, while contributing to Azure deployments, CI/CD, and production observability. Collaboration and rigorous testing are emphasized throughout.

Qualifications

• 3-5 years as backend/full-stack engineer, AI engineer, or data scientist.
• Bachelor's degree in CS, Software Eng, AI/ML, or related field.

Responsibilities

• Design and build AI-powered applications with agentic orchestration and LLM integrations.
• Own prompt architecture, tool definitions, and orchestration flow.
• Design evaluation frameworks and run structured experiments.
• Own Azure infrastructure and deployment pipelines for AI workloads.
• Build robust CI/CD pipelines using Azure DevOps.
• Monitor production AI apps and drive incidents to resolution.
• Stay updated on LLM and agentic AI developments.
• Collaborate to raise engineering standards and document findings.

Skills

Python

C#

REST APIs

Microservices

LLM prompting

LangChain

Semantic Kernel

Azure AI

GitHub Copilot

Experiment design

DevOps

Kubernetes

Education

Bachelor's in CS

Tools

Docker

Kubernetes

Bicep

Terraform

Azure DevOps

GitHub Copilot

Job description

Talent500 is hiring for one of its clients.

About Itineris:

Itineris is a global technology company headquartered in Belgium, dedicated to delivering innovative software and services for the energy and water utility sector. Our flagship solution, UMAX, is a Microsoft Dynamics 365-based CIS and ERP platform used by leading utilities across North America and Europe. As a long-standing Microsoft Gold Partner and member of Microsoft’s Inner Circle, we are deeply embedded in the Microsoft ecosystem and actively building the next generation of AI-native capabilities on top of it.

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
• 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 with agentic development workflows using tools like GitHub Copilot, Claude Code, or similar
• Experience designing or running structured experiments on LLM or agentic systems
• Ability to define evaluation criteria, build scoring rubrics, and reason systematically about output quality
• Familiarity with eval approaches (LLM-as-judge, human evaluation, automated regression testing)
• Hands-on experience with Azure (ACA/AKS, Azure Storage, Azure Monitoring, App Insights, ...)
• Infrastructure as Code with Bicep (or Terraform, with willingness to learn)
• Containerization with Docker; experience with Kubernetes is a plus
• Building and maintaining CI/CD pipelines for containerized workloads through Azure DevOps

Analytical Thinking:

• Rigorous and curious: you form clear hypotheses before drawing conclusions
• Comfortable with ambiguity and able to communicate findings clearly to both technical and non-technical stakeholders

Education & Experience:

• 3-5 years of demonstrable experience as a backend/full-stack software engineer, AI engineer, or data scientist
• Degree in Computer Science, Software Engineering, AI/ML, or a related discipline

Preferred Qualifications:

• Experience with MCP, A2A, or other agent integration patterns
• Familiarity with Copilot Studio or similar low-code agent orchestration platforms
• Exposure to the Microsoft Dynamics 365 / Power Platform ecosystem
• Experience with monitoring and observability tools
• Microsoft Certified: Azure Developer Associate or DevOps Engineer Expert
• Experience contributing to or evaluating open-source LLM tooling
• Publications, conference talks, or public writing on applied AI topics are a plus