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