Senior Software Engineer, Data (AI)
New
CanadaFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 4–7 years
- Required Skills
- AWSRedshiftPrompt EngineeringLLMDistributed Systems
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.
Responsibilities
- 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.
View Full Description & ApplyYou'll be redirected to the employer's site
