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Juniper Square

Unified platform for private investment partnerships

Senior Staff Software Engineer - AI

Platform EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • An advanced degree in Computer Science, Engineering, or a related field is required.
  • At least 15 years of experience in distributed systems, platform engineering, or infrastructure roles.
  • Proven experience architecting large-scale, high-availability, multi-tenant distributed systems in production.
  • Strong hands-on experience with modern cloud-native stacks, including Kubernetes, containers, service mesh, and serverless technologies.
  • Deep expertise in distributed systems fundamentals, including consistency models, consensus, partitioning, idempotency, backpressure, and failure modes.
  • Advanced proficiency in Python, Go, Java, or a similar language, along with strong systems-level debugging skills.
  • Expertise in infrastructure as code, such as Terraform or Pulumi, and modern continuous integration and delivery.
  • Experience designing event-driven and streaming architectures, such as Kafka.
  • Experience building developer platforms, internal tooling, or paved-road infrastructure at scale.
  • Strong understanding of observability practices and Site Reliability Engineering principles, including service-level objectives, error budgets, and incident management.
  • Hands-on experience with AWS, Azure, or Google Cloud Platform at production scale.
  • Strong understanding of infrastructure security, multi-tenancy, and compliance best practices.
  • Ability to operate at both executive and deeply technical levels.

Responsibilities

  • Define and own end-to-end systems architecture strategy across services, infrastructure, and the developer platform.
  • Design frameworks and design patterns that accelerate the work of the engineering organization.
  • Design scalable, fault-tolerant distributed systems spanning synchronous application programming interfaces, asynchronous workflows, and event-driven architectures.
  • Establish standards for service design, application programming interface contracts, multi-tenancy, and inter-service communication.
  • Lead architecture reviews and technical decision-making for high-stakes, cross-cutting initiatives.
  • Drive adoption of modern architectures, including event-driven systems, platform engineering, and infrastructure as code.
  • Design and prototype critical platform and infrastructure components.
  • Write production-quality code for complex or high-impact areas.
  • Review service designs, infrastructure changes, and performance-critical code paths.
  • Troubleshoot performance, scalability, and reliability issues across services, queues, caches, and databases.
  • Optimize workloads for latency, throughput, concurrency, and cost.
  • Design and architect a scalable cloud platform supporting compute, networking, storage, service orchestration, and deployment across product lines.
  • Build a paved-road developer platform with golden paths, internal tooling, continuous integration and delivery, and self-service infrastructure.
  • Create reusable platform primitives and internal application programming interfaces that product teams can compose.
  • Enable self-service infrastructure for engineering teams through standardized patterns, templates, and platform capabilities.
  • Partner with artificial intelligence workflow teams, product teams, and security teams to support production artificial intelligence workloads, from inference pipelines to agent fleets.
  • Design systems for safe agentic execution, including isolation boundaries, resource governance, auditability, and human-in-the-loop controls.
  • Ensure platform reliability, scalability, and resilience, including high availability, monitoring, and disaster recovery readiness.
  • Architect core systems to handle the data volumes and structural complexity of large managers, including thousands of entities, tens of thousands of limited partners, and deep multi-tier fund structures.
  • Define scalability targets and re-architect bottlenecked systems ahead of demand to ensure performance at ten times current transaction and data volumes.
  • Design enterprise integration surfaces, including application programming interfaces, bulk data interfaces, and enterprise resource planning/general ledger connectivity, for large institutional general partners.
  • Meet enterprise security, compliance, and operational diligence expectations, such as single sign-on/system for cross-domain identity management, granular entitlements, audit trails, and data residency.
  • Serve as the senior technical voice in enterprise sales and onboarding conversations where architecture, scale, and resiliency are decision criteria.
  • Lead incident response maturity, including on-call practices, blameless postmortems, and systemic remediation.
  • Drive capacity planning, load testing, and chaos and resilience engineering practices.
  • Optimize cloud spend through architecture, workload placement, and continuous cost engineering.
  • Mentor senior engineers across platform, infrastructure, and product teams.
  • Partner with product, data, and business teams to align systems investments with company outcomes, including the GPX upmarket expansion.
  • Translate business and product requirements into scalable, operable system designs.
  • Influence roadmaps using platform, reliability, and cost considerations.
  • Act as the executive technical authority for systems architecture and production engineering.
  • Evangelize artificial intelligence adoption, including artificial intelligence-assisted engineering and operations.
  • Promote a culture of operational excellence and outcome-driven innovation.
  • Serve as a role model for engineering excellence across the organization.

Desired Qualifications

  • Experience taking a software-as-a-service platform upmarket to serve large enterprise or institutional customers.
  • Background in private markets, fund accounting, or fintech systems with complex financial domain models.
  • Experience building infrastructure for artificial intelligence/large language model workloads, including inference serving, agent runtimes, graphics processing unit scheduling, or evaluation systems.
  • Background in high-growth software-as-a-service, fintech, or other regulated, data-sensitive environments.
  • Experience with large-scale cloud cost optimization.
  • Experience scaling relational databases, such as PostgreSQL, under high concurrency.

About the Company

Juniper Square

Unified platform for private investment partnerships

Juniper Square provides end-to-end software for private investment partnerships, serving general partners and limited partners in commercial real estate, private equity, and venture capital. Its platform unifies fundraising, investor operations, and fund administration into a single system to manage investment data and workflows from start to finish. The product centralizes secure data sharing, tracks investor communications, automates tasks, and offers a 360-degree view of investment data to speed investment closes. It differentiates itself with a universal, purpose-built system for private markets that scales for firms of all sizes and structures, aiming to simplify and accelerate the private investment process for both GP and LP users.

Company size
1,001-5,000
Company stage
Series D
Total funding
$371M
Headquarters
San Francisco, CA
Founded
2014

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