Principal AI Engineer

Overview

Develop and scale secure, reliable, cloud-native AI-enabling platform services, public APIs and SDKs for AI adoption across AVEVA’s product portfolio and partner ecosystem. Work as part of a Scrum team to build standards-compliant, secure and production-grade AI capabilities.

What you'll do

• Build scalable, fault-tolerant cloud-native services on Microsoft Azure, ensuring high performance and reliability.
• Develop secure, well-documented public APIs and SDKs for consumption by internal and external developers.
• Collaborate with cross-functional teams to deliver end-to-end solutions across data pipelines, orchestration, and service APIs.
• Embed robust security controls to protect sensitive data and ensure secure access to AI services.
• Contribute to design reviews, code reviews, and architectural discussions to ensure engineering excellence.
• Mentor junior developers, encourage continuous learning, and contribute to a culture of innovation.
• Work with multiple teams to create AI solutions, including AI model deployment, training, and AI tooling development.

What you'll need

• 8+ years of professional software engineering experience, including 3+ years working directly on AI/ML systems or platforms.
• Hands-on experience with Microsoft Azure and associated PaaS services, such as Azure Functions, AKS, and API Management.
• Strong expertise in RESTful API design, versioning, testing, and lifecycle management.
• Proficiency in securing APIs, managing authentication/authorization, and applying data privacy practices.
• Excellent problem-solving skills, with the ability to analyse complex technical challenges and propose scalable solutions.
• Experience working in Agile teams and collaborating across global R&D locations.
• Demonstrated ability to mentor junior team members, fostering a culture of continuous learning and innovation.
• Demonstrated experience with AI frameworks, tools and Python.
• Experience working with Large Language Models (LLMs) and understanding of trade-offs between performance, cost, and capability.
• Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling.
• Experience with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A).
• Strong knowledge or experience working with various ML algorithms, including regression, classification, clustering, and deep learning.
• Knowledge of AI ethics and regulations, such as NIST AI RMF and EU AI Act, and commitment to responsible AI development.
• Fluency in developing code using AI tools such as GitHub Copilot.
• Ability to use prompt engineering to carry out multiple development tasks.
• Familiarity with AI orchestration, including tools like AI Foundry and/or Semantic Kernel, MAF.

Nice to have

• Experience with tools for automated testing and evaluation of AI outputs.

Details

• Location: Bangalore, India.
• Employment type: Regular, Full-Time.
• The role is described as hybrid, with most roles based at a local AVEVA office and an expectation of being on-site 50% of working hours; the working arrangement for this position will be confirmed during the hiring process.