Senior Software Engineer, Platform

Juniper Square is an operations partner for private markets that unifies technology, data, and fund administration services into a single platform. The Senior Software Engineer will build and operate foundational platform infrastructure powering the company’s AI initiatives, while driving technical excellence, collaborating cross-functionally, and developing reliable production systems.

Responsibilities:

• Design, build, and ship production-quality systems, APIs, and services - from foundational platform capabilities to customer-facing product experiences
• Own projects end-to-end: translating requirements into technical designs, implementation, testing, deployment, and ongoing iteration
• Build reliable, scalable, and observable systems that deliver value to customers and enable other engineering teams to move faster
• Own the production health of the systems you build, including monitoring, troubleshooting, performance, reliability, and issue resolution
• Build reusable infrastructure, frameworks, tooling, and developer experiences that enable teams across the organization
• Improve engineering velocity and operational quality through automation, documentation, and continuous improvements
• 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
• Help identify and reduce technical debt, reliability risks, and friction in the software development lifecycle
• Collaborate with Staff and senior engineers to establish reusable patterns and raise engineering standards
• Participate in code reviews, design reviews, debugging, incident response, and operational support
• 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, shipping quality output regardless of how it was produced
• Build or integrate AI/LLM-powered capabilities in your domain where they add real value (e.g., evaluation frameworks, RAG pipelines, agentic workflows), with clear human-in-the-loop boundaries
• Contribute to the team's evolving practices around AI-accelerated development, testing, and code review
• Work closely with product, design, QA, and cross-functional partners to meet timelines and align solutions to business goals
• Provide clear, accessible technical context to both technical and non-technical stakeholders
• Grow into a subject-matter expert with a deep understanding of the data, workflows, and customer needs specific to that space

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
• Background in financial services or fintech
• Experience with API gateway/infrastructure, security & governance tooling, retrieval and data-access systems, or agent frameworks at production scale