Senior Software Engineer, Data (AI)

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Software Engineer, Data (AI) in Canada.

This is a high-impact opportunity to help build a next-generation AI-native data platform designed to transform complex financial operations at scale. In this role, you will work at the intersection of modern data engineering, backend development, and applied AI, contributing to the architecture and delivery of intelligent data pipelines used by institutional clients. You will join a collaborative, high-performing engineering environment where innovation, ownership, and technical excellence are deeply valued. The position offers the chance to work on greenfield systems, influence foundational technical decisions, and shape the future standards of a rapidly evolving platform. Ideal candidates are hands-on engineers who thrive in fast-paced environments, enjoy solving challenging technical problems, and are excited about leveraging AI-assisted development workflows. This role combines strong technical depth with meaningful product impact in a globally distributed and digital-first organization.

• Design, build, and maintain production-grade data pipeline components including schema mapping, normalization, validation, enrichment, and distribution workflows.
• Develop clean, scalable, and well-tested backend services, APIs, and data infrastructure supporting a modern intelligent data platform.
• Take full ownership of features and systems from technical design through deployment, monitoring, and production support.
• Collaborate closely with senior and staff engineers to shape architecture decisions related to AI-native data warehousing and scalable financial data systems.
• Contribute to schema design, API standards, normalization strategies, and platform reliability improvements across the engineering organization.
• Leverage AI-assisted and agentic development workflows to accelerate engineering productivity while ensuring code quality, correctness, and maintainability.
• Build and maintain data quality controls, monitoring systems, observability tooling, and validation frameworks to support reliable large-scale operations.
• Participate in incident response and on-call rotations, troubleshooting and resolving data pipeline and system issues efficiently.
• Create and maintain technical documentation to support engineering best practices, knowledge sharing, and operational excellence.

Requirements:

• 4–7 years of software engineering experience with a strong track record of delivering production systems end-to-end.
• Strong expertise in backend engineering, data pipelines, API development, and scalable distributed systems.
• Hands-on experience with ETL/ELT workflows, schema design, data normalization, and data warehouse engineering practices.
• Practical experience integrating and deploying LLM-based solutions, including prompt engineering, model integration, and AI output validation.
• Strong familiarity with AI-assisted development and agentic coding workflows as part of day-to-day engineering practices.
• Experience with AWS cloud infrastructure and modern data platforms; familiarity with Redshift is considered an advantage.
• Ability to critically assess AI-generated code, identify regressions, and ensure production-quality output.
• Excellent written communication skills with the ability to document technical decisions clearly for engineering and product stakeholders.
• Experience with vector databases, RAG pipelines, document extraction systems, or AI evaluation frameworks is considered a strong plus.
• Background in financial services data, institutional reporting, or investment operations is beneficial.
• Strong problem-solving mindset, ownership mentality, and ability to thrive in collaborative, fast-paced environments.

Benefits:

• Competitive compensation package including base salary, equity opportunities, and performance-driven growth potential.
• Comprehensive health, dental, and vision coverage for employees and their families.
• Mental wellness support and employee well-being programs.
• Fertility, family-building, parental leave, medical leave, and bereavement support programs.
• Flexible paid time off policy in addition to company-paid holidays.
• Retirement savings plans designed to support long-term financial security.
• Home office and technology setup allowance to support remote and hybrid work flexibility.
• Annual professional development stipend for continued learning, certifications, and career growth.
• Flexible work arrangements within a digital-first and globally distributed work environment.
• Opportunity to work on cutting-edge AI and data engineering initiatives with a highly collaborative engineering team.