Lead AI Engineer - Cloud & Platform Services at AVEVA

📍 Job Overview

Job Title: Lead AI Engineer - Cloud & Platform Services
Company: AVEVA
Location: Cambridge, England, United Kingdom
Job Type: Regular, Full-Time
Category: AI Engineering, Cloud & Platform Services
Date Posted: 2025-08-09
Experience Level: 10+ years
Remote Status: Hybrid (3 days in-office)

🚀 Role Summary

Key Web Technology Aspects:
- Design, develop, and scale AI-enabling platform services and public APIs on Microsoft Azure.
- 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.

💻 Primary Responsibilities

AI & Cloud Engineering:
- 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.
AI Model Deployment & Orchestration:
- Work with multiple teams to create AI solutions, which include AI model deployment, training, and AI tooling development.
- Understand and apply AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A).
- Familiarize yourself with AI orchestration tools like AI Foundry and/or Semantic Kernel.
Mentoring & Collaboration:
- Mentor junior developers, encourage continuous learning, and contribute to a culture of innovation.
- Work with multiple teams to create AI solutions, which include AI model deployment, training, and AI tooling development.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Artificial Intelligence, or a related field. A Master's degree would be an asset.

Experience: 8+ years of professional software engineering experience, including 3+ years working directly on AI/ML systems or platforms.

Required Skills:

Strong expertise in RESTful API design, versioning, testing, and lifecycle management.
Proficient in securing APIs, managing authentication/authorization, and data privacy practices.
Excellent problem-solving skills, with the ability to analyze 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.

Preferred Skills:

Experience with tools for automated testing and evaluation of AI outputs.
Familiarity with AI ethics and regulations (e.g., NIST AI RMF, EU AI Act), and commitment to responsible AI development.
Experience 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.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate your experience with AI model deployment, training, and AI tooling development through relevant projects.
Showcase your API development skills with examples of secure, well-documented public APIs and SDKs.
Highlight your problem-solving skills and ability to analyze complex technical challenges through case studies or live demos.

Technical Documentation:

Provide clear and concise documentation for your AI projects, including code comments, version control, and deployment processes.
Include testing methodologies, performance metrics, and optimization techniques used in your projects.

💵 Compensation & Benefits

Salary Range: £70,000 - £90,000 per annum (based on market research for AI Engineering roles in Cambridge, UK)

Benefits:

Flexible benefits fund
Emergency leave days
Adoption leave
28 days annual leave (plus bank holidays)
Pension
Life cover
Private medical insurance
Parental leave
Education assistance program

Working Hours: 40 hours per week, with flexible working hours and remote work options available.

🎯 Team & Company Context

🏢 Company Culture

Industry: AVEVA operates in the industrial software sector, focusing on industrial automation and engineering products.

Company Size: AVEVA has over 6,500 employees in over 40 countries, with a global team of 2000+ developers working on over 75 industrial automation and engineering products.

Founded: 1967 (as CADDS, later merged with Tribon and acquired by Schneider Electric in 2018, now a standalone company)

Team Structure:

The Core AI Services team is part of AVEVA's R&D organization, working closely with various product teams to deliver AI solutions.
The team consists of AI engineers, data scientists, and software developers, collaborating to build innovative, standards-compliant, secure, and production-grade AI capabilities.

Development Methodology:

Agile methodologies, with a focus on rapid prototyping, continuous improvement, and the agility of a start-up.
Collaborative development practices, including code reviews, architectural discussions, and knowledge sharing.
A culture of innovation, learning, and inclusivity, with a structured focus on learning and collaboration.

Company Website: AVEVA

📝 Enhancement Note: AVEVA's company culture emphasizes learning, collaboration, and innovation, fostering a supportive environment for AI engineers to grow and excel.

📈 Career & Growth Analysis

AI Engineering Career Level: Lead AI Engineer roles involve significant technical leadership, mentoring, and collaboration with cross-functional teams. They require a deep understanding of AI/ML systems, cloud-native architectures, and API development.

Reporting Structure: Lead AI Engineers typically report to a Senior Manager or Director within the R&D organization. They may also collaborate with product managers, project managers, and other stakeholders to deliver end-to-end AI solutions.

Technical Impact: Lead AI Engineers have a significant impact on AVEVA's product portfolio and partner ecosystem by designing, developing, and scaling AI-enabling platform services and public APIs. These services act as foundational building blocks for AI adoption across AVEVA's products.

Growth Opportunities:

Technical Leadership: Progress to Senior AI Engineer or AI Architect roles, focusing on architecture decisions, technical strategy, and mentoring more junior team members.
Product Management: Transition into a product management role, focusing on AI product strategy, roadmap development, and stakeholder communication.
Entrepreneurship: Explore opportunities to spin off AI-focused startups or intrapreneurship initiatives within AVEVA.

📝 Enhancement Note: AVEVA offers strong growth opportunities for AI engineers, with clear paths to technical leadership, product management, and entrepreneurship.

🌐 Work Environment

Office Type: A hybrid work environment, with employees expected to be in their local AVEVA office three days a week.

Office Location(s): Cambridge, United Kingdom (with global R&D locations supporting collaboration across time zones)

Workspace Context:

AVEVA's Cambridge office is located in the Science Park, providing a modern and collaborative workspace for its employees.
The office features multiple monitors, testing devices, and development tools to support AI engineering tasks.
The workspace encourages cross-functional collaboration between developers, designers, and stakeholders, fostering a culture of knowledge sharing and continuous learning.

Work Schedule: Flexible working hours, with core hours between 10:00 AM and 4:00 PM GMT. Remote work options are available, with a focus on maintaining work-life balance.

📝 Enhancement Note: AVEVA's hybrid work environment balances the need for collaboration and knowledge sharing with the flexibility to work remotely and maintain a healthy work-life balance.

📄 Application & Technical Interview Process

Interview Process:

Technical Phone Screen: A 30-45 minute phone or video call to assess your AI engineering skills, API development experience, and problem-solving abilities.
On-site Technical Assessment: A half-day on-site assessment, including a technical deep dive into your AI engineering portfolio, a coding challenge, and a system design exercise.
Behavioral & Cultural Fit Interview: A 45-60 minute interview to assess your cultural fit, communication skills, and problem-solving approach.
Final Decision & Offer: A final decision and offer, subject to successful background checks and drug screening.

Portfolio Review Tips:

Highlight your experience with AI model deployment, training, and AI tooling development through relevant projects.
Showcase your API development skills with examples of secure, well-documented public APIs and SDKs.
Demonstrate your problem-solving skills and ability to analyze complex technical challenges through case studies or live demos.

Technical Challenge Preparation:

Brush up on your AI engineering skills, with a focus on cloud-native architectures, API development, and AI/ML systems.
Practice coding challenges and system design exercises to prepare for the on-site technical assessment.
Familiarize yourself with AVEVA's products and the industrial software sector to demonstrate your understanding of the business context.

ATS Keywords:

AI Engineering, Cloud Services, Microsoft Azure, API Development, RESTful APIs, Machine Learning, Python, Agile Methodologies, Mentoring, Collaboration, AI Ethics, AI Orchestration, Large Language Models, Retrieval-Augmented Generation, Agent Orchestration, Prompt Engineering, Tool Calling, AI Frameworks, Automated Testing, AI Standards, Model Context Protocol, Agent2Agent, Responsible AI Development, AI Regulations, NIST AI RMF, EU AI Act.

📝 Enhancement Note: AVEVA's interview process focuses on assessing technical skills, problem-solving abilities, and cultural fit, with a strong emphasis on AI engineering and API development.

🛠 Technology Stack & Web Infrastructure

AI & Cloud Technologies:

Microsoft Azure (Azure Functions, AKS, API Management)
Python (PyTorch, TensorFlow)
AI Frameworks & Tools (GitHub Copilot, AI Foundry, Semantic Kernel)
AI Standards (Model Context Protocol, Agent2Agent)
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Agent Orchestration, Prompt Engineering, Tool Calling

API Development & Security:

RESTful API Design, Versioning, Testing, and Lifecycle Management
API Security, Authentication/Authorization, and Data Privacy Practices

Collaboration & Development Tools:

Agile Methodologies (Scrum, Kanban)
Version Control (Git)
Continuous Integration/Continuous Deployment (CI/CD) Pipelines
Project Management Tools (Jira, Azure DevOps)

📝 Enhancement Note: AVEVA's technology stack emphasizes Microsoft Azure, Python, and AI-specific frameworks and tools, with a strong focus on cloud-native architectures and API development.

👥 Team Culture & Values

AI Engineering Values:

Innovation: Embrace a culture of continuous learning, experimentation, and innovation in AI engineering.
Collaboration: Foster a collaborative environment, working closely with cross-functional teams to deliver end-to-end AI solutions.
Responsibility: Uphold high ethical standards and commit to responsible AI development, ensuring the security, privacy, and fairness of AI systems.
Quality: Strive for excellence in AI engineering, with a focus on robust, secure, and scalable AI solutions.

Collaboration Style:

Cross-Functional Integration: Work closely with developers, designers, and stakeholders to deliver AI solutions that meet user needs and business objectives.
Code Review Culture: Encourage peer programming, knowledge sharing, and continuous learning through code reviews and architectural discussions.
Mentoring & Knowledge Sharing: Foster a culture of mentoring and knowledge sharing, with a focus on technical skill development and career growth.

📝 Enhancement Note: AVEVA's AI engineering values emphasize innovation, collaboration, responsibility, and quality, with a strong focus on cross-functional integration and mentoring.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Scalability & Performance: Design and develop AI-enabling platform services and public APIs that are secure, reliable, and cloud-native, ensuring high performance and scalability.
Security & Compliance: Embed robust security controls to protect sensitive data and ensure secure access to AI services, adhering to relevant regulations and industry standards.
AI Orchestration: Work with AI orchestration tools like AI Foundry and/or Semantic Kernel to deploy, train, and manage AI models at scale.
AI Ethics & Responsibility: Ensure the ethical and responsible development of AI systems, with a focus on privacy, fairness, and transparency.

Learning & Development Opportunities:

AI Specialization: Deepen your expertise in AI engineering, with a focus on cloud-native architectures, API development, and AI/ML systems.
Emerging Technologies: Stay up-to-date with the latest AI trends, tools, and frameworks, exploring opportunities to work with cutting-edge AI technologies.
Leadership Development: Develop your leadership skills, with a focus on mentoring, team management, and architecture decisions.
Industry Engagement: Engage with the AI engineering community, attending conferences, webinars, and meetups to network and learn from industry peers.

📝 Enhancement Note: AVEVA offers significant technical challenges and growth opportunities for AI engineers, with a strong focus on scalability, security, AI orchestration, and ethical AI development.

💡 Interview Preparation

Technical Questions:

AI Engineering Fundamentals: Demonstrate your understanding of AI engineering principles, AI/ML systems, and cloud-native architectures.
API Development & Security: Showcase your expertise in RESTful API design, versioning, testing, and lifecycle management, as well as API security, authentication/authorization, and data privacy practices.
Problem-Solving: Solve complex technical challenges, demonstrating your ability to analyze problems, propose scalable solutions, and communicate your approach effectively.

Company & Culture Questions:

AI Engineering Culture: Demonstrate your understanding of AVEVA's AI engineering values, collaboration style, and commitment to responsible AI development.
AI Engineering Methodologies: Showcase your experience with Agile methodologies, code reviews, and architectural discussions, with a focus on delivering high-quality AI solutions.
AI Engineering Impact: Explain how your AI engineering skills and experience can contribute to AVEVA's product portfolio and partner ecosystem, driving AI adoption and innovation.

Portfolio Presentation Strategy:

AI Engineering Portfolio: Highlight your experience with AI model deployment, training, and AI tooling development through relevant projects.
API Development Portfolio: Showcase your API development skills, with examples of secure, well-documented public APIs and SDKs.
Problem-Solving Portfolio: Demonstrate your problem-solving skills and ability to analyze complex technical challenges through case studies or live demos.

📝 Enhancement Note: AVEVA's interview preparation focuses on assessing technical skills, problem-solving abilities, and cultural fit, with a strong emphasis on AI engineering and API development.

📌 Application Steps

To apply for this AI Engineering role at AVEVA, follow these steps:

Tailor Your Resume: Highlight your AI engineering experience, API development skills, and problem-solving abilities. Include relevant keywords and phrases to optimize your resume for AVEVA's Applicant Tracking System (ATS).
Prepare Your Portfolio: Showcase your AI engineering projects, API development examples, and problem-solving case studies. Ensure your portfolio is up-to-date, well-organized, and easy to navigate.
Research AVEVA: Familiarize yourself with AVEVA's products, industry context, and company culture. Prepare thoughtful questions to ask during the interview process, demonstrating your interest in the role and the company.
Practice Technical Challenges: Brush up on your AI engineering skills, API development, and problem-solving abilities. Practice coding challenges and system design exercises to prepare for the on-site technical assessment.
Prepare for Behavioral & Cultural Fit Interviews: Reflect on your work experience, identifying examples of your problem-solving skills, collaboration, and adaptability. Prepare stories and anecdotes that illustrate your fit with AVEVA's AI engineering values and culture.

By following these steps and demonstrating your AI engineering expertise, API development skills, and cultural fit, you'll be well-prepared to succeed in the application and interview process for this exciting AI Engineering role at AVEVA.

Lead AI Engineer - Cloud & Platform Services