## About the Company

Juniper Square is a financial technology company focused on the private markets industry. It provides technology, data, and fund administration services to general partners (GPs) and investment organizations.

According to the job posting, Juniper Square:

- Serves 2,300+ GPs.
- Has $300B+ under administration.
- Has 700,000+ limited partners (LPs) on its platform.
- Has 1,000+ employees.
- Was founded in 2014.
- Has raised $350M+ in funding.
- Offers JunieAI, its AI platform for private-market workflows.

The company operates across the U.S., Canada, India, Luxembourg, and England, with offices including San Francisco, New York City, Mumbai, and Bangalore.

## About the Role

Job Title: Senior Staff Software Engineer — AI

Department: Engineering

Employment: Full-time

Location: Americas — Remote, preferably EST

Travel: Required occasionally

This is a very senior, hands-on engineering leadership role. The engineer will own the architecture and evolution of Juniper Square's core distributed systems, cloud infrastructure, developer platform, and AI infrastructure.

The role is not simply an AI/ML coding position. It combines:

Software Architecture + Distributed Systems + Cloud Infrastructure + Platform Engineering + AI Infrastructure + Technical Leadership The engineer will help prepare the platform to support extremely large private-equity customers managing $100B+ in assets under management (AUM).

## What You Will Do

### Architecture & Technical Leadership

- Define the company's systems architecture strategy.
- Design scalable and fault-tolerant distributed systems.
- Establish standards for APIs and service communication.
- Design multi-tenant architectures.
- Lead architecture reviews.
- Make high-impact technical decisions.
- Drive adoption of event-driven architectures.
- Promote platform engineering and Infrastructure-as-Code practices.

### Hands-On Engineering
- Prototype critical infrastructure components.
- Write production-quality code.
- Review complex code and system designs.
- Troubleshoot scalability and reliability problems.
- Optimize latency, throughput, concurrency, and cloud costs.
- Work with services, queues, caches, and databases.

### Platform & Cloud Infrastructure
- Design scalable cloud platforms.
- Build internal developer platforms.
- Create golden paths and reusable engineering patterns.
- Develop internal tools and APIs.
- Build CI/CD capabilities.
- Enable self-service infrastructure for engineering teams.
- Create standardized infrastructure templates.

### AI Infrastructure A major component of this role is supporting JunieAI and agentic workloads.





Responsibilities include

- Supporting AI inference pipelines.
- Supporting fleets of AI agents.
- Designing safe agent execution environments.
- Creating isolation boundaries.
- Managing AI resource usage.
- Building auditability into agentic systems.
- Implementing human-in-the-loop controls.

### Enterprise Scale The engineer will prepare systems for very large institutional customers.

This includes

- Scaling systems to 10× current transaction and data volumes.
- Supporting thousands of entities and tens of thousands of LPs.
- Handling complex multi-tier fund structures.
- Building enterprise APIs.
- Supporting bulk data interfaces.
- Supporting ERP/GL integrations.
- Designing SSO/SCIM capabilities.
- Implementing granular permissions.
- Supporting audit trails and data residency requirements.

### Reliability
- Improve incident response.
- Establish mature on-call practices.
- Conduct blameless postmortems.
- Drive systemic remediation.
- Perform capacity planning.
- Conduct load testing.
- Implement resilience/chaos engineering.
- Improve disaster recovery.
- Optimize cloud spending.

## Qualifications The provided section does not yet show a complete formal qualification list, but the responsibilities make clear that the candidate needs very deep senior-level engineering experience.

The idóneo candidate should have strong experience with:

- Distributed systems.
- Cloud infrastructure.
- Platform engineering.
- Service architecture.
- APIs.
- Event-driven systems.
- Infrastructure as Code.
- CI/CD.
- Production software engineering.
- Scalability and reliability.
- Observability.
- Multi-tenant systems.
- Enterprise security.
- AI/agent infrastructure.

## Skills

### Core Engineering

- Distributed systems
- Software architecture
- Production software development
- Microservices/service architecture
- API design
- Event-driven architecture
- Asynchronous workflows
- Synchronous APIs
- Databases
- Caching
- Queues
- Concurrency
- Performance optimization

### Cloud & Platform
- Cloud infrastructure
- Platform engineering
- Infrastructure as Code
- CI/CD
- Developer platforms
- Self-service infrastructure
- Internal APIs
- Infrastructure automation
- Cloud cost optimization
- Monitoring and observability

### AI




- AI infrastructure
- AI inference pipelines
- Agentic AI
- AI agent fleets
- Agent isolation
- Resource governance
- Auditability
- Human-in-the-loop systems

### Enterprise & Security
- Multi-tenancy
- SSO
- SCIM
- Access control
- Granular entitlements
- Audit trails
- Data residency
- Enterprise integrations
- ERP/GL connectivity
- Security and compliance

### Leadership
- Technical leadership
- Architecture reviews
- Mentoring senior engineers
- Cross-functional collaboration
- Executive communication
- Technical strategy
- Incident leadership
- Operational excellence

## Requirements

### Most Important Requirements The strongest signals from the posting are:

Senior Staff-level engineering experience + distributed systems + cloud/platform architecture + hands-on coding + scalability + reliability + AI infrastructure + technical leadership

This position requires someone who can design the architecture and also build it.

It is specifically described as a deeply hands-on leadership role, so this is not a purely managerial Staff/Principal position.

## Work Arrangement

- Remote across the Americas.
- Preferably Eastern Time Zone (EST).
- Full-time.
- Some travel required.
- Travel may include leadership meetings, team offsites, and customer engagements.

## Equal Opportunity The provided portion of the does not include a specific Equal Opportunity Employer statement. Therefore, a detailed EEO policy cannot be confirmed from the information provided.

## Quick Summary

This is an extremely senior platform/infrastructure engineering role with a major AI component.

### Top Resume Keywords

Senior Staff Software Engineer | Distributed Systems | Cloud Architecture | Platform Engineering | Infrastructure as Code | Event-Driven Architecture | Microservices | API Design | CI/CD | Developer Platform | Kubernetes/Cloud Infrastructure | Scalability | Reliability | Observability | Multi-Tenancy | AI Infrastructure | Agentic AI | Inference Pipelines | Security | SSO/SCIM | Disaster Recovery | Cost Optimization | Technical Leadership

### What Makes This Role Different

Despite the “AI” label, the position is primarily about building the systems foundation that allows AI and other products to operate reliably at enterprise scale.

If your background is mainly Data Science, ML modeling, or Python-based analytics, this would likely be a weaker match. If your background is Staff/Principal Software Engineering, distributed systems, cloud platforms, and infrastructure—with AI/agent systems experience, it is much closer to the target profile.

📌 Software Engineer, Sr. (AI) (México)
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