Our mission is to unlock the full potential of private markets. Privately owned assets like commercial real estate, private equity, and venture capital make up half of our financial ecosystem yet remain inaccessible to most people. We are digitizing these markets, and as a result, bringing efficiency, transparency, and access to one of the most productive corners of our financial ecosystem. If you care about making the world a better place by making markets work better through technology – all while contributing as a member of a values-driven organization – we want to hear from you.
Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.
About the RoleWe are looking for a Senior Technical Lead to architect, build, and scale mission-critical, public-facing APIs. This role combines deep hands-on engineering with technical leadership, architectural ownership, and mentorship.
You will define backend standards, guide system design decisions, and ensure our APIs are secure, scalable, and resilient. You are expected to operate at both strategic and execution levels — setting direction while remaining technically hands-on.
What you'll doArchitecture & System Design
Own end-to-end architecture of public-facing API platforms
Design scalable, multi-tenant, distributed systems with high availability
Drive API standards: versioning, backward compatibility, documentation, governance
Define security, rate limiting, and abuse prevention strategies
Lead performance optimisation and reliability initiatives
Engineering Execution
Build and review high-quality backend services using Python and FastAPI
Architect and optimise asynchronous systems using Celery
Design and tune complex schemas and queries in PostgreSQL
Lead production readiness, observability, and incident response improvements
Drive AWS infrastructure architecture decisions
Technical Leadership
Mentor backend engineers and raise engineering standards
Lead design reviews and establish coding best practices
Partner with Product, Frontend, DevOps, and Data teams
Drive the technical roadmap and manage technical debt strategically
Influence long-term platform scalability decisions
9.5-12 years of backend engineering experience with strong production ownership
Deep expertise in Python/Java and modern API frameworks (FastAPI preferred)
Proven experience designing and scaling public-facing APIs
Strong system design expertise (distributed systems, scalability, fault tolerance)
Extensive experience with PostgreSQL (performance tuning, indexing, transactions)
Strong experience with Celery or distributed task processing systems
Hands-on experience with Redis and caching strategies
Advanced experience with AWS (ECS/EKS, RDS, Lambda, S3, API Gateway, networking)
Experience implementing secure API architectures (OAuth2, JWT, RBAC, WAF)
Experience with Docker, CI/CD pipelines, and Infrastructure as Code
Experience operating high-traffic, production-critical systems
Experience designing multi-tenant or external partner APIs
Strong Differentiators and AI Experience
Experience leading backend teams in a product-driven environment
Experience designing API platforms consumed by third parties
Frontend exposure (React / Next.js / TypeScript)
Experience with GraphQL
Experience building developer platforms or SDKs
Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases introduced by AI-assisted development
Experience building and shipping production-grade software using AI-assisted workflows across the full SDLC
Hands-on experience developing or integrating LLM-powered systems (e.g., agents, copilots, tool-using workflows, or multi-step reasoning systems)
Familiarity with patterns such as tool-calling agents, planning/execution loops, and retrieval-augmented generation (RAG)
Demonstrated ability to leverage modern AI tools to improve development velocity, code quality, and problem-solving
Experience contributing to AI-powered features (e.g., intelligent search, conversational interfaces, recommendations, automation)
Working knowledge of LLMs, embeddings, semantic search, and RAG pipelines
Ability to identify and evaluate opportunities to integrate AI capabilities into products and workflows
