Senior Software Engineer, AI-Native Data Warehouse

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer, AI-Native Data Warehouse based in Canada.

As a Senior Software Engineer, you will design, build, and operate production systems powering a customer-facing AI-native data warehouse.

You will work on data extraction and an evolving pipeline that moves from ingestion and parsing through classification and structured extraction.

The role combines deep backend engineering with hands-on work across RAG pipelines, vectorized storage, AI agents, and data infrastructure.

You will own complex projects end-to-end, from technical design and implementation through deployment, observability, and continuous improvement.

Working closely with product, design, QA, and senior engineering peers, you will help establish scalable patterns and raise engineering standards.

You will also play a key role in shaping an AI-native software development lifecycle, using AI tools thoughtfully while maintaining rigorous quality and reliability.

This is an opportunity to solve complex problems in an evolving technical environment where your decisions can directly influence both the product and engineering practices.

Accountabilities:

• Design, build, test, deploy, and operate production-quality systems, APIs, and services across foundational platform capabilities and customer-facing experiences.
• Own projects end-to-end, translating business and product requirements into technical designs, implementation plans, testing strategies, deployments, and ongoing improvements.
• Build reliable, scalable, observable systems that deliver meaningful customer value and enable other engineering teams to move faster.
• Take ownership of production health, including monitoring, troubleshooting, performance optimization, reliability, and incident resolution.
• Develop intuitive and performant product experiences that address customer needs and support measurable business outcomes.
• Improve engineering velocity and operational quality through automation, documentation, reusable patterns, and continuous process improvements.
• Contribute to technical design for complex initiatives, evaluating tradeoffs and developing pragmatic, maintainable implementation approaches.
• Partner with product, design, QA, and engineering stakeholders to translate requirements into effective technical solutions.
• Identify and reduce technical debt, reliability risks, and friction throughout the software development lifecycle.
• Participate in code reviews, design reviews, debugging, incident response, and ongoing operational support.
• Use agentic coding tools and AI-assisted development as an integral part of the engineering workflow, determining when AI is the right tool and when traditional approaches are more appropriate.
• Critically review AI-generated code for correctness, edge cases, regressions, security, and maintainability.
• Build and integrate AI/LLM-powered capabilities such as evaluation frameworks, RAG pipelines, agentic workflows, and human-in-the-loop systems where they provide meaningful value.
• Contribute to evolving team practices around AI-assisted development, testing, code review, and engineering quality.
• Communicate technical concepts and tradeoffs clearly to both technical and non-technical stakeholders.
• Develop deep domain expertise in the AI-native data warehouse, its underlying data, workflows, and customer requirements.

Requirements:

• 7+ years of experience in backend and/or full-stack software engineering.
• Strong backend engineering experience with Python and frameworks such as FastAPI, Flask, Pyramid, or Django.
• Experience working with relational and NoSQL databases, including schema design, query optimization, and data modeling.
• Hands-on experience with cloud-native technologies such as AWS, Docker, and Kubernetes, as well as infrastructure-as-code practices.
• Strong understanding of CI/CD, observability, and operating production services reliably at scale.
• Ability to work across the full stack when required; TypeScript and React experience is a plus.
• Demonstrated ability to break down complex technical problems and deliver pragmatic, maintainable solutions.
• Strong ownership mindset, with the ability to independently drive projects while collaborating effectively across teams.
• Excellent communication skills and the ability to explain technical decisions and tradeoffs clearly to engineering and cross-functional stakeholders.
• Hands-on experience with AI-native development tools such as Cursor or Augment, along with a thoughtful perspective on when AI should and should not be used.
• Experience adapting code review and engineering practices for AI-generated code, including safeguards against over-reliance on AI tooling.
• Hands-on experience building or integrating AI/LLM-powered systems in production, such as RAG pipelines, agent frameworks, evaluation workflows, guardrails, prompt or tool orchestration, or model observability.
• Comfort working in ambiguous and rapidly evolving technical environments where established patterns and best practices are still emerging.
• Bachelor’s degree in Computer Science or equivalent professional experience.
• Strong data warehousing or data engineering expertise is a plus, particularly with platforms such as Redshift, Snowflake, BigQuery, or Databricks.
• Experience delivering AI-focused data pipeline or data warehousing solutions is advantageous.
• Comfort working in early-stage or less prescriptive environments where engineers are expected to help define the right approach.
• Strong collaboration skills and a willingness to contribute to an inclusive, diverse, and high-performing engineering culture.

Benefits:

• Base salary range of CAD $165,000 to CAD $190,000, with actual compensation determined by experience, skills, location, and applicable local requirements.
• Equity compensation.
• Health, dental, and vision coverage for employees and their families.
• Life insurance.
• Mental wellness coverage.
• Fertility and growing family support.
• Flex Time Off in addition to company-paid holidays.
• Paid family leave, medical leave, and bereavement leave.
• Retirement savings plans.
• Allowance to customize your home working and technology setup.
• Annual professional development stipend.
• Flexible ways of working, including remote and digital-first collaboration options.
• Inclusive environment that values diverse perspectives, open communication, and continuous learning.