Data & AI Solutions Engineer

About the role

We are seeking a Data & AI Solutions Engineer to design, build, and scale enterprise-grade data and AI solutions across UTIMCO's Microsoft ecosystem. This role combines software engineering, cloud technologies, data engineering, and generative AI to deliver intelligent applications that enhance investment decision-making, operational efficiency, and business processes.

Responsibilities

• Data Engineering & Integration
• Design, develop, and maintain scalable enterprise data pipelines using Azure Data Factory, Databricks, and Azure-native services.
• Build reusable data integration and transformation frameworks supporting structured and unstructured data.
• Generative AI Solutions
• Integrate Azure OpenAI Service capabilities into enterprise applications within UTIMCO's secure Azure environment.
• Design and implement Retrieval-Augmented Generation (RAG) solutions using approved enterprise data sources.
• Develop prompt engineering, evaluation, testing, and monitoring processes that support quality, traceability, and responsible AI deployment.
• Application Development, Cloud Engineering & DevOps
• Design, develop, and deploy full-stack applications using modern web technologies and Microsoft-centric development tools.
• Implement and maintain CI/CD pipelines and deployment workflows using Azure DevOps.
• Ensure solutions meet enterprise standards for security, performance, observability, reliability, and operational readiness.
• Business Partnership & Solution Delivery
• Take ownership of solutions throughout their lifecycle by partnering with stakeholders to continuously enhance functionality, usability, and business value.
• Partner directly with investment, risk, and operational teams to identify opportunities for workflow automation and business process improvement.
• Translate business requirements into scalable technical architectures and iterative implementation roadmaps.
• Influence solution design through close partnership with business stakeholders and iterative delivery of high-value capabilities.
• Drive adoption through hands-on development, stakeholder collaboration, and continuous feedback loops.
• Governance, Responsible AI & Engineering Excellence
• Apply secure-by-design principles and established governance practices throughout the software development lifecycle.
• Support responsible and ethical use of data and AI technologies through transparency, monitoring, governance controls, and auditability.
• Balance rapid experimentation with disciplined software engineering practices, including automated testing, documentation, monitoring, release management, and operational support.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent hands-on software development experience demonstrating strong coding ability.
• 4+ years of professional software engineering experience, or equivalent practical experience, designing, developing, or supporting software applications, cloud solutions, or data platforms.
• Experience developing applications using Azure or AWS, with an interest in working within a Microsoft Azure ecosystem.
• Experience working in a modern software development environment using Agile methodologies, including sprint planning, task boards, daily standups, source control, and collaborative code reviews.
• Familiarity with Git, GitHub or Azure DevOps, branching strategies, continuous integration, and continuous deployment (CI/CD) practices.
• Experience developing full-stack applications using technologies such as React, TypeScript, .NET, or comparable modern development frameworks.
• Experience partnering with business users, customers, or stakeholders to understand business needs and translate them into technical solutions.
• Experience working with enterprise data, analytics, APIs, or cloud-native applications. Experience with financial or investment data is helpful but not required.
• Exposure to AI, machine learning, or generative AI technologies, including using AI-assisted development tools to improve productivity and software delivery.
• Familiarity with application security, identity management, testing, debugging, and software engineering best practices.
• Strong analytical and problem-solving skills with a passion for learning new technologies and continuously improving.
• Excellent written, verbal, and interpersonal communication skills, with the ability to collaborate effectively across technical and non-technical teams.
• Demonstrated initiative, curiosity, and ownership.

Preferred Qualifications

• Hands-on experience with Azure Data Factory, Databricks, and Microsoft-native analytics solutions.
• AI- or cloud-related certifications (e.g., Microsoft Azure, Azure AI, or Databricks) are a plus.
• Experience operating in financial services, institutional investment management, or other regulated environments.
• Experience implementing Retrieval-Augmented Generation (RAG) architectures and enterprise search solutions.
• Experience developing evaluation, monitoring, and governance frameworks for AI-enabled applications.
• Familiarity with production support, observability, monitoring, and incident response practices.
• Knowledge of responsible AI principles, data governance, and ethical use of AI technologies.
• Experience with Azure DevOps and modern DevOps practices.
• Experience working in a dynamic, collaborative, and team-oriented atmosphere.