Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Director, Engineering (Platform)
- Salary
- USD 230k–285k / yr
- Department
- Software Engineering
- Employment
- Full Time
- Experience
- Director
- Published
- Apply before
- 8 Dec 2026
- Listing views
- 53
- Application actions
- 2
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About this role.
About Juniper Square
Private markets are one of the largest, most complex, and most underserved corners of global finance. Our mission at Juniper Square is to unlock their full potential. We’re the Operations Partner trusted by 2,300+ GPs, unifying technology, data, and fund administration services into a single platform that helps GPs move faster, make better decisions, and scale with precision. With $300B+ under administration and 700,000+ LPs on platform, we’ve built the scale to match our ambition. And with JunieAI, our purpose-built AI platform, we’re reimagining how private markets operate, embedding intelligence across every workflow. Founder-led since 2014, backed by $350M+ in funding, and now 1,000+ employees strong, we’re building a company designed to shape the future of private markets for decades to come.
Our culture is built for people who want to do ambitious, meaningful work alongside exceptionally talented teammates. We think like owners, move with urgency, and take pride in solving hard problems that truly matter to our customers and the future of private markets. We believe the best ideas come from open debate, deep collaboration, and diverse perspectives, which is why we believe transparency is the default and feedback makes us stronger. If you’re energized by high standards, rapid growth, and the opportunity to help define a category at a pivotal moment, come join us!
Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time.
About your role
As the Director, Engineering you will lead the vision and execution for the foundational systems that power our entire engineering organization. Your mandate spans four critical pillars: architecting the modularization of our core Python/FastAPI monolith, accelerating our transition to an AI-native engineering culture, empowering product teams with tools to build AI-enabled features, and establishing a robust Application Security (AppSec) posture.
You will manage a group of engineering managers and staff engineers. You will act as a strategic multiplier for the company, treating our internal platform as a top-tier product. Your ultimate goal is to create secure, high-velocity “paved paths” that make our product teams incredibly fast, while systematically reducing technical debt and security risks.
What you’ll do
Direct the Monolith Evolution: Own the multi-year technical strategy to safely decouple our legacy Python/Jinja monolith into a modern, modular FastAPI architecture using Domain-Driven Design and zero-downtime database migration tactics.
Drive the AI-Native SDLC: Champion the rollout and adoption of AI-assisted coding tools and AI-augmented workflows across the entire engineering organization, systematically measuring and improving developer productivity.
Enable AI Feature Development: Treat the internal platform as a product. Guide the development of intuitive SDKs, data pipelines, and internal tools that reduce cognitive load and allow product engineers to easily integrate LLMs and build AI-powered features.
Lead Application Security (AppSec): Champion a “shift-left” security culture. Embed secure coding practices, automated vulnerability scanning, and threat modeling directly into developer workflows, ensuring our core platform is resilient against modern threats.
Oversee Core Shared Services: Drive the scale, security, and reliability of enterprise-critical systems, including Identity (AuthN/AuthZ, OAuth2, RBAC), Audit Logs, and high-throughput API & MCP Gateways.
Navigate Org-Wide Boundaries: Negotiate complex refactoring timelines with Product leaders and collaborate seamlessly with other Engineering teams and DevOps to align our platform capabilities with infrastructure.
Build a World-Class Organization: Recruit, mentor, and grow a high-performing organization of engineering managers and staff/principal engineers, fostering a culture of architectural pragmatism and deep developer empathy.
Qualifications
15+ years of software engineering experience, with at least 5+ years in engineering leadership, including explicitly managing managers and leading multiple teams.
High AI Fluency: Proven experience architecting systems that support AI features (LLMs, RAG, tool calling) and a track record of driving AI-assisted development tools (AI SDLC) across engineering teams.
An executive track record of successfully guiding massive monolith-to-modular migrations and decoupling shared database schemas in high-traffic, business-critical environments.
Deep strategic understanding of Application Security principles, Identity/Access Management (OAuth 2.0, OIDC), and modern API traffic management.
Strong technical fluency in Python and FastAPI ecosystems, with the ability to guide Staff-level engineers through complex architectural decisions involving both modern APIs and legacy applications.
Exceptional executive communication skills, with the ability to translate complex technical, security, and AI trade-offs into business value.
Compensation
Compensation for this position includes a base salary, bonus, equity and a variety of benefits. The U.S. base salary range is $230,000 – $285,000 USD. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable.
Benefits include:
Health, dental, and vision care for you and your family
Life insurance
Mental wellness coverage
Fertility and growing family support
Flex Time Off in addition to company-paid holidays
Paid family leave, medical leave, and bereavement leave policies
Retirement saving plans
Allowance to customize your work and technology setup at home
Annual professional development stipend
Your recruiter can provide additional details about compensation and benefits.
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Sample interview questions
I would begin by mapping domains, dependencies, ownership, and database coupling, then establish a sequenced migration roadmap around high-value bounded contexts. I would use incremental extraction patterns, compatibility layers, observability, feature flags, and zero-downtime migration practices so teams can validate each step while continuing normal delivery.
I would define a balanced scorecard that combines adoption and workflow metrics with quality outcomes. Measures could include cycle time, pull-request throughput, developer sentiment, review quality, escaped defects, security findings, and the time required to complete representative engineering tasks; I would avoid relying on code volume alone.
It embeds security into the paved path rather than creating a late-stage gate. I would prioritize secure defaults in libraries and templates, automated dependency and code scanning, threat modeling for material changes, clear remediation ownership, and risk-based escalation supported by security champions and actionable developer feedback.
I would treat AI enablement as an internal platform product with well-documented SDKs, approved model access, retrieval and evaluation tooling, identity-aware authorization controls, auditability, and guardrails for data handling. Product teams should be able to use a supported path without each independently solving model routing, observability, security, and prompt evaluation.
I would translate technical investments into product outcomes such as faster delivery, reliability, reduced incident risk, or support for strategic AI capabilities. By publishing a transparent roadmap, defining measurable milestones, and jointly prioritizing constraints and dependencies, platform and product leaders can make explicit trade-offs rather than treating foundational work as invisible overhead.
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