Senior Staff Software Engineer (AI)

Juniper Square provides technology, data, and fund administration services for private markets. The Senior Staff Software Engineer will lead the architecture and evolution of distributed services, cloud infrastructure, and developer platforms, while designing scalable systems for enterprise growth, AI workloads, reliability, security, and operational excellence.

Responsibilities:

• Define and own the end-to-end systems architecture strategy across services, infrastructure, and developer platform
• Designing frameworks and design patterns that accelerate the work of the rest of engineering org
• Design scalable, fault-tolerant distributed systems spanning synchronous APIs, asynchronous workflows, and event-driven architectures
• Establish standards for service design, API 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 (event-driven systems, platform engineering, 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 all product lines
• Build a paved-road developer platform — golden paths, internal tooling, CI/CD, and self-service infrastructure — that makes the right way the easy way
• Create reusable platform primitives and internal APIs that product teams can compose rather than rebuild
• Enable self-service infrastructure for engineering teams through standardized patterns, templates, and platform capabilities
• Partner with AI workflow teams, product, and security teams to support production AI 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 reliability, scalability, and resilience of the platform, including high availability, monitoring, and disaster recovery readiness
• Architect core systems to handle the data volumes and structural complexity of $100B+ AUM managers: thousands of entities, tens of thousands of LPs, and deep multi-tier fund structures
• Define scalability targets and re-architect bottlenecked systems ahead of demand, ensuring performance holds at 10x current transaction and data volumes
• Design enterprise integration surfaces — APIs, bulk data interfaces, and ERP/GL connectivity — that fit into the existing technology estates of large institutional GPs
• Meet the security, compliance, and operational diligence expectations of the largest PE firms, such as, SSO/SCIM, 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: on-call practices, blameless postmortems, and systemic remediation
• Drive capacity planning, load testing, and chaos/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 AI adoption, including AI-assisted engineering and operations
• Help promote a culture of operational excellence and outcome-driven innovation
• Become a role model for engineering excellence for the rest of the org

Requirements:

• Advanced degree in Computer Science, Engineering, or related field
• 15+ years 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 (Kubernetes, containers, service mesh, serverless)
• Deep expertise in distributed systems fundamentals: consistency models, consensus, partitioning, idempotency, backpressure, and failure modes
• Advanced proficiency in Python, Go, Java, or similar; strong systems-level debugging skills
• Expertise in infrastructure as code (Terraform, Pulumi, or similar) and modern CI/CD
• Experience designing event-driven and streaming architectures (Kafka or similar)
• Experience building developer platforms, internal tooling, or paved-road infrastructure at scale
• Strong understanding of observability practices and SRE principles (SLOs, error budgets, incident management)
• Hands-on experience with AWS, Azure, or GCP at production scale
• Strong understanding of infrastructure security, multi-tenancy, and compliance best practices
• Ability to operate at both executive and deeply technical levels
• Experience taking a SaaS 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 AI/LLM workloads: inference serving, agent runtimes, GPU scheduling, or evaluation systems
• Background in high-growth SaaS, fintech, or other regulated, data-sensitive environments
• Experience with large-scale cloud cost optimization
• Experience scaling relational databases (PostgreSQL or similar) under high concurrency