POSITION OVERVIEW

The Senior Digital / AI Engineer designs, builds, and scales advanced digital and AI-driven solutions that create measurable business impact. This role combines strong software engineering skills with applied machine learning, and modern cloud-native architectures. The Senior Engineer acts as a technical leader, translating business problems into robust, production-grade AI systems while mentoring junior engineers and influencing platform standards.

Key responsibilities will include the following:

• New Requests/Builds
  • Collaborating on solutions with Solution Architects and other supporting IT areas.
• Provide technical advice and guidance to assigned business area teams.
• Be a consultant/analyst on strategic projects.
• Lead initiatives that span strategy and road map exercises, architecture definition, product selection, application and integration design and implementation.
• Responsible for the entire lifecycle of IT Solutions, including regular maintenance, patching, updates, and fixes.
• Manages all aspects of the technical activities (including software development requirements, architectural requirements, hardware, technical models, vendor interaction, technical designs, etc.) and ensures the solutions and applications align with the overall architecture and infrastructure.
• Participate in testing and verification of technical solutions.
• Communicate the effectiveness and task progress of the technical project team members.
• Design, develop, and deploy AI/ML-powered applications and digital platforms in production environments.
  • Implement end-to-end AI systems, including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
  • Implement scalable APIs, microservices, and event-driven architectures supporting AI workflows.
  • Ensure solutions meet security, privacy, and compliance r
  • Establish engineering best practices: testing, CI/CD, observability, and documentation.
  • Contribute to reusable libraries, internal platforms, and reference architectures.
  • Apply machine learning, deep learning, NLP, or generative AI techniques where appropriate.
  • Work with structured and unstructured data at scale.
  • Collaborate with data scientists to productionize models and experiments.
  • Implement MLOps practices: versioning, model lifecycle management, drift detection, and retraining.
• General Support
  • Partner with product managers, business stakeholders, third-party administrators, and domain experts to define AI use cases.
  • Translate ambiguous business problems into technical solutions and delivery plans.
  • Mentor junior engineers and review code and designs.
  • Act as a technical point of contact for complex AI initiatives.
  • Manage and facilitate all incidents from Priority 1 to Priority 4, which includes, but not limited to, providing support to users of applications, responding to user-based questions, tickets and assists with troubleshooting issues within applications.
  • Manage day-to-day operational and tactical aspects of multiple projects or requests.

Education

• Bachelor’s degree in an IT related field or similar combination or education and experience.

Skills

• A quick learner of software and information technology and motivated to learn new applications and business operations.
• Proven experience working with technology vendors.
• Ability to conceptualize and articulate ideas clearly and concisely.
• Ability to interact and communicate with business stakeholders at different levels in the organization.
• Demonstrates excellent documentation skills.
• Self-disciplined, able to work independently, but also able to take direction when necessary.
• Self-motivated to identify and resolve issues and in advancing personal knowledge.
• Very organized and detail-oriented.
• Flexible with time working in a fast-paced, matrixed environment.
• Strong ability to understand the business problem and come up with efficient AI driven solutions. It should not be a solution searching for a problem and must lean on simplicity. Also ensuring the solution meets business needs, easy to adopt, scalable, fast, and secure.

Required Experience

• 3–5+ years of experience in software engineering, data engineering, or AI/ML engineering.
• Proven experience delivering production AI or advanced digital systems.
• Hands-on development primarily in Python, including building and integrating AI/ML services.
• Hands-on experience deploying systems in cloud environments (AWS, Azure).
• Experience designing and building robust integrations (REST APIs, webhooks, event-driven patterns) between internal and third-party systems.
• Solid understanding of data pipelines, databases, and distributed systems.
• Familiarity with MLOps tools and practices (CI/CD, model monitoring, orchestration)
• Strong system design and problem-solving skills.
• Ability to balance speed, quality, and scalability
• Comfortable working with incomplete requirements and evolving priorities.

Preferred Qualifications

• Experience with generative AI, LLMs, and prompt engineering.
• Background in a regulated or enterprise environment.
• Experience influencing technical standards or leading complex initiatives.