Principal, Lead Engineer AI

Quality Assurance

• Defines and embeds appropriate testing and validation approaches for AI/ML solutions, including model evaluation and performance testing.
• Ensures that monitoring and benchmarking practices are in place so that models perform reliably and consistently in production.
• Supports the implementation of processes to identify and address model drift, data issues, and potential bias.
• Promotes a culture of quality within squads, ensuring solutions meet business requirements and relevant regulatory standards.
• Represents the team in internal and selected external technical forums where appropriate, contributing to knowledge sharing and continuous improvement.

Operations, Maintenance, Support, and Documentation

• Leads the implementation of MLOps practices within their area, supporting efficient model deployment, monitoring, and lifecycle management.
• Ensures that CI/CD practices are applied to AI/ML workflows to improve delivery speed and reliability.
• Oversees the ongoing performance of production AI systems within their scope, addressing issues related to scalability and stability.
• Ensures that appropriate documentation is in place for models, datasets, and key technical decisions, supporting maintainability and transparency.

Data and Architecture

• Contributes to the evolution of AI/ML architecture within their area, ensuring solutions are scalable, efficient, and aligned with enterprise direction.
• Guides the optimisation of data pipelines, feature stores, and model serving approaches to support effective AI delivery.
• Supports the evaluation and adoption of cloud-based AI/ML services, ensuring choices are aligned with technical and business requirements.
• Ensures that ethical AI principles and security considerations are embedded in solution design and implementation.

Knowledge, Skills, Experience & Qualifications

• Holds a degree in Computer Science, Machine Learning, or a related technical field, or equivalent industry experience, with a strong focus on AI and ML systems.
• Brings significant hands-on experience developing and delivering production-grade AI/ML solutions within cloud environments, ideally Azure.
• Proven ability to design, implement, and support resilient AI/ML solutions in production environments, ensuring reliability and scalability.
• Demonstrates strong practical experience with Azure-based AI services, including Azure OpenAI, AI Search, and AI Studio.
• Well-versed in modern machine learning approaches, MLOps practices, and cloud-based AI architectures.
• Proficient in Python, common machine learning frameworks, distributed processing concepts, and core MLOps practices.
• Experience designing APIs, building microservices, and implementing end-to-end ML pipelines on cloud platforms.
• Demonstrates experience of cloud platforms such as Azure and AWS, with experience supporting and maintaining cloud-based infrastructure.
• Hands-on experience working with:
  • LLM-based solutions, including Retrieval-Augmented Generation techniques and prompt engineering approaches
  • Data processing frameworks and platforms, including batch and streaming pipelines
  • Practical understanding of MLOps processes, including model lifecycle management, deployment approaches, monitoring, and performance optimisation.
  • Experience supporting model serving, feature engineering, and solution optimisation to meet performance and accuracy requirements.
  • Clear understanding of AI ethics, model governance, and explainability principles, and their application in delivery.
  • Ability to contribute to technical direction and support alignment across teams, working effectively with Product Owners, architects, and engineering leads.
  • Strong understanding of cloud security fundamentals, compliance considerations, and cost awareness when delivering AI/ML solutions.
  • Fluent in spoken and written English, with an ability to work effectively across diverse and multicultural teams.
  • Able to communicate clearly with both technical and non-technical stakeholders, tailoring messages to the audience.
  • Confident in making informed technical decisions within their scope, considering delivery constraints, risks, and longer-term implications.
  • Experience contributing to the adoption of coding standards, CI/CD practices, and quality approaches within teams.
  • Experience contributing to technical documentation, knowledge sharing, and internal communities of practice.
  • Demonstrates strong team leadership behaviours, supporting and mentoring engineers, and contributing to a positive and collaborative engineering culture.
  • Experience working with data engineering processes, model training workflows, and real-time or near real-time AI solutions.
  • Understanding of data governance practices and regulatory considerations relevant to AI/ML delivery.

What is it like to work at the EBRD? / About EBRD

Our agile and innovative approach is what makes life at the EBRD a unique experience! You will be part of a pioneering and diverse international organisation, and use your talents to make a real difference to people's lives and help shape the future of the regions we invest in.

At EBRD, our Values – Inclusiveness, Innovation, Trust, and Responsibility – are at the heart of how we work. We bring these to life through our Workplace Behaviours: listening well and speaking up, collaborating smartly, acting decisively with full commitment, and simplifying to amplify our impact. These principles shape our culture and define our success. We seek individuals who not only share these values but are also committed to embedding them in their daily work, fostering a positive and high-performing environment.

The EBRD Environment Provides You With

• Varied, stimulating, and engaging work that gives you an opportunity to interact with a wide range of experts in the financial, political, public, and private sectors across the regions we invest in.
• A working culture that embraces inclusion and celebrates diversity. Our workforce reflects a broad range of backgrounds, perspectives, and experiences, bringing fresh ideas, energy, and innovation and enhancing our ability to serve our clients, shareholders, and counterparties effectively.
• A hybrid workplace that offers flexibility to teams and individuals; that is based on trust, flexibility, and connectedness.
• An environment that places sustainability, equality, and digital transformation at the heart of what we do.
• A workplace that prioritises employee wellbeing and provides a comprehensive suite of competitive benefits.

Diversity is one of the Bank’s core values which are at the heart of everything it does. As such, the EBRD seeks to ensure that everyone is treated with respect and given equal opportunities and works in an inclusive environment. The EBRD encourages all qualified candidates who are nationals of the EBRD member countries to apply regardless of their racial, ethnic, religious and cultural background, gender, gender identity, sexual orientation, age, socio-economic background, or disability.

Please note, that due to the high volume of applications received, we