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Salary: CAD 165,000 - 190,000 / annual
Juniper Square is a fintech platform serving private markets, with $300B+ under administration and 1,000+ employees. The company operates across 27 U.S. states, 2 Canadian provinces, India, Luxembourg, and England, with physical offices in San Francisco, New York City, Mumbai, and Bangalore.
You will join Dex, Juniper Square's AI-native data warehouse—a customer-facing data product powering core workflows for institutional financial clients. As a Senior Software Engineer, you are a hands-on individual contributor designing, building, and operating production systems. You'll own projects end-to-end: translating requirements into technical designs, implementation, testing, deployment, and ongoing iteration.
Key responsibilities include:
• Design, build, and ship production-quality systems, APIs, and services from foundational platform capabilities to customer-facing product experiences
• Own the production health of systems you build, including monitoring, troubleshooting, performance, reliability, and incident resolution
• Work on data extraction pipelines (Ingest → Parse → Classify → Extract), owning initial MVP agents covering structured data extraction, RAG pipelines, vectorized storage, and documentation repositories
• Contribute to technical design for complex projects, evaluating tradeoffs and proposing pragmatic implementation plans
• Partner with product, design, and engineering to translate requirements into well-designed technical solutions
• Use agentic coding tools and AI-assisted development as a primary part of your workflow, deliberately choosing where AI versus traditional software is the right tool
• Critically evaluate AI-generated code for correctness, edge cases, and regressions
• Build or integrate AI/LLM-powered capabilities where they add real value (e.g., evaluation frameworks, RAG pipelines, agentic workflows)
• Work closely with product, design, QA, and cross-functional partners to meet timelines and align solutions to business goals
• Grow into a subject-matter expert in Dex, with deep understanding of data, workflows, and customer needs
• Help identify and reduce technical debt, reliability risks, and friction in the software development lifecycle
• Improve engineering velocity through automation, documentation, and continuous improvements
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 with relational/NoSQL databases, including schema design, query optimization, and data modeling
• Experience with cloud-native technologies such as AWS, Docker, and Kubernetes, and infrastructure as code
• Strong understanding of CI/CD, observability, and operating services in production
• Comfort working full-stack when the problem calls for it (TypeScript/React experience a plus)
• Ability to break down complex technical problems and deliver pragmatic, maintainable solutions
• Strong ownership mindset, with the ability to drive projects independently while collaborating effectively across teams
• Clear communication skills, with the ability to explain technical tradeoffs to engineering and cross-functional partners
• Hands-on experience with AI-native development tools (e.g., Cursor, Augment), and demonstrated AI fluency: a deliberate point of view on when AI is (and isn't) the right tool, adapted code review practices for AI-generated code, and safeguards against over-reliance on AI tooling
• Bachelor's degree in Computer Science or equivalent work experience
• Hands-on experience building or integrating AI/LLM-powered systems in production (e.g., RAG pipelines, agent frameworks, evaluation workflows, guardrails, prompt/tool orchestration, or model observability)
• Comfort operating in ambiguous, fast-evolving technical territory where best practices and patterns are still being established
Nice to have:
• Strong data warehousing or data engineering expertise (Redshift, Snowflake, BigQuery, Databricks)
• Experience shipping AI-forward data pipeline or warehousing solutions
• Comfort navigating ambiguity in an early-stage, less spec-heavy environment
