Senior Staff Software Engineer (AI)

Juniper Square•,

1d•$265,000•Remote

About The Position

We are seeking a Senior Staff Software Engineer to lead the architecture and evolution of the core systems that power Juniper Square — the distributed services, cloud infrastructure, and developer platform on which every product, workflow, and AI capability is built. You will define the vision, architecture, operating model, and execution roadmap required to evolve from team-by-team infrastructure decisions to a cohesive, paved-road platform that enables every engineering team to ship reliable, secure, and performant software at speed. This role anchors a strategic priority for our GPX line of business: taking Juniper Square upmarket to serve the largest private equity institutions in the world — firms managing $100B+ in AUM. Serving these PE titans demands a step-change in everything our systems do: order of magnitude increase in data and traffic volumes; enterprise-grade security, and integration expectations. You will architect the systems foundation that makes this scalable. This is a deeply hands-on leadership role for a technical expert who leads by building: you will actively design systems, prototype solutions, write and review code, and guide teams through their most complex technical challenges. Your mandate spans the full systems estate. You will modernize our service architecture and cloud foundation, define architecture across compute, networking, service communication, multi-tenancy, and observability, and build the systems substrate — including the infrastructure powering JunieAI and agentic workloads — on which teams across the business build and operate software. Throughout, you will hold our production systems to the availability, latency, security, and cost standards expected of a platform administering $300B+ in private markets assets. You will work closely with engineering leadership, product teams, security, and executive stakeholders to align technology strategy with business outcomes, mentor engineers, and build a culture of operational excellence. Success in this role means not only delivering a modern systems platform but also elevating the team's capabilities, processes, and ways of working to operate as a true platform engineering organization. While this is a remote role, some travel is required — to in-person leadership meetups, team offsites, and to customer sites in support of enterprise engagements where deep technical presence matters.

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

Nice To Haves

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

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