Principal Software Engineer (AI & Data Products)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Software Engineer (AI & Data Products) based in Canada (Remote).

As a Principal Software Engineer, you will provide hands-on technical leadership in designing and building scalable software, data, and AI-powered products supporting critical clinical research workflows. You will drive architectural strategy across product lines, ensuring systems are reliable, secure, maintainable, and aligned with long-term business objectives. Working at the intersection of software engineering, data architecture, and artificial intelligence, you will lead the development of intelligent document processing, information extraction pipelines, and agentic AI applications. You will collaborate with Product, Data Science, Infrastructure, and Engineering teams to deliver high-impact technical initiatives and establish reusable engineering practices. In addition to solving complex architectural challenges, you will mentor senior engineers and influence technical decisions across the organization. This role offers an opportunity to advance healthcare innovation through robust, production-ready AI and data solutions.

Accountabilities:

As a Principal Software Engineer, you will serve as a technical authority responsible for architecture, engineering excellence, and the delivery of sophisticated software and AI solutions. You will translate strategic architectural direction into practical implementations, lead complex cross-functional initiatives, and ensure the long-term performance, scalability, security, and reliability of critical systems.

• Drive technical strategy and architectural decisions across one or more product lines, ensuring alignment with enterprise architecture, engineering standards, and business objectives.

• Own end-to-end product-line architecture, designing scalable, reliable, secure, and maintainable systems that follow broader organizational guidelines.

• Translate high-level architectural strategies into actionable technical designs and implementation plans for engineering teams.

• Lead complex, high-impact technical initiatives involving multiple teams, systems, and product components.

• Establish and reinforce engineering best practices, architectural patterns, and design standards to ensure consistency and quality across teams.

• Collaborate with architects to implement and refine technical direction, providing feedback based on practical engineering constraints and production system behavior.

• Resolve highly complex technical challenges involving system scale, ambiguity, performance, and cross-team dependencies.

• Lead architectural and design reviews, evaluating solutions against long-term scalability, performance, reliability, and maintainability requirements.

• Influence technical prioritization and engineering trade-offs, balancing business needs with architectural standards and long-term objectives.

• Mentor and develop senior and staff-level engineers, strengthening technical decision-making, system design capabilities, and engineering excellence.

• Identify and address systemic risks, technical debt, performance bottlenecks, and operational inefficiencies across product lines.

• Drive improvements in system reliability, observability, monitoring, and operational excellence.

• Evaluate and introduce new technologies, ensuring their adoption supports architectural standards and long-term technical strategy.

• Champion application security by implementing security strategies, identifying vulnerabilities, and coordinating remediation efforts based on security scans and penetration testing results.

• Collaborate with Product, Quality Assurance, Support, Cloud, Architecture, Infrastructure, and Data Science teams to ensure cohesive delivery and high-quality outcomes.

• Act as the primary technical authority for assigned product lines, designing transformative solutions with broader organizational impact.

• Architect reliable data pipelines with clearly defined data contracts, schema evolution strategies, end-to-end data lineage, versioning, and idempotent processing.

• Build and productionize document processing and information extraction pipelines, agentic AI applications, and automated evaluation frameworks.

• Establish end-to-end observability across data quality, pipeline reliability, model performance, and inference costs, including longitudinal metrics and automated regression detection.

• Optimize model selection and inference orchestration to balance output quality, latency, throughput, and operational costs.

• Partner with Data Science, Architecture, and Infrastructure teams to develop reusable engineering patterns, shared tools, and clear operational ownership.

Requirements:

The ideal candidate is a highly experienced software engineering leader with extensive expertise in distributed systems, backend technologies, cloud platforms, and modern data architectures. You should have a proven ability to own complex technical architectures, guide engineering teams, and transform emerging AI and machine learning capabilities into reliable production solutions. Strong strategic thinking, technical judgment, and collaboration skills are essential.

• Bachelor's degree in Information Systems, Computer Science, Engineering, or a related discipline, or equivalent professional experience.

• 15+ years of software engineering experience, including substantial experience in senior or staff-level positions with increasing technical leadership responsibilities.

• Proven experience designing and owning architecture for complex, mission-critical distributed systems.

• Deep expertise in modern backend and/or web technologies, including several of the following:

• Python, Java, Ruby on Rails, or .NET.

• Modern frontend frameworks and web technologies.

• Distributed systems and API design.

• Cloud platforms, databases, and scalable software architectures.

• Demonstrated ability to guide technology selection, architectural decisions, and engineering standards across teams or product areas.

• Experience mentoring and developing senior and staff-level engineers while influencing engineering best practices.

• Strong understanding of scalable system design, high availability, performance optimization, and fault-tolerant architectures.

Preferred Qualifications:

• Experience developing software in healthcare, life sciences, or other highly regulated industries, with familiarity with HIPAA, FDA, or comparable compliance requirements.

• Working knowledge of clinical trial processes and medical informatics.

• Hands-on experience designing, developing, and deploying applications on AWS, including cloud-native services.

• Proven experience designing high-scale, highly available systems and optimizing distributed application performance.

• Experience implementing observability practices, including logging, monitoring, distributed tracing, and alerting.

• Strong background in designing and operating production data pipelines and distributed data processing systems.

• Experience with automated testing, continuous integration and delivery (CI/CD), cloud deployment, and production monitoring.

• Demonstrated ability to take AI and machine learning workflows from prototypes to reliable, scalable production systems.

• Strong understanding of data architecture and modeling, schema design and evolution, data quality management, and data lineage.

• Experience with AI-powered information extraction, agentic applications, model evaluation, or inference orchestration.

Benefits:

• Competitive annual base salary ranging from C$180,000 to C$243,000.

• Potential eligibility for an additional variable performance bonus.

• Health coverage and employee benefits.

• Paid holidays.

• Fully remote working opportunity for candidates based in Canada.

• Opportunity to lead strategic engineering initiatives involving advanced AI, data products, and distributed systems.

• Meaningful contribution to technology solutions that support clinical research and advance human health.

• Collaborative environment focused on innovation, technical excellence, and continuous improvement.

• Opportunity to mentor experienced engineers and influence architectural decisions across multiple product areas.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1