Staff Software Engineer (AI)
Juniper Square5 months ago
Base Salary
$210k - $260k/yr
Responsibilities
- Set technical direction and architecture for shared AI SDKs, guardrails, evaluation frameworks, feedback systems, and agentic workflow infrastructure
- Own technical strategy and hands-on implementation of complex backend and AI platform systems from design through production
- Design and operate LLM-powered systems, including RAG pipelines, agentic workflows, evaluation infrastructure, guardrails, and model observability
- Write production code as a hands-on individual contributor and own end-to-end AI system reliability
- Define quality benchmarks, evaluation frameworks, and feedback loops to improve AI output accuracy and reliability
- Champion AI-native development practices and tools such as Cursor and Augment while maintaining correctness and reliability
- Mentor engineers, improve technical decision-making, and establish coding standards, review practices, and architectural documentation
- Partner with recruiting to build and grow the engineering team
- Collaborate with engineering managers, product, design, and QA on technical plans, design reviews, and roadmap discussions
- Resolve cross-team conflicts and technical decisions autonomously
Requirements
- 7+ years of backend and/or ML engineering experience with increasing technical leadership, architectural responsibility, and mentorship
- A portfolio of shipped production systems and the ability to explain personally made technical decisions and written code
- Deep expertise in Python and strong proficiency building production-grade backend services
- Experience with other server-side languages such as Node/TS or Java is a plus
- Production experience building and operating AI- and LLM-powered systems such as AI SDKs, RAG pipelines, evaluation frameworks, agentic workflows, or model observability
- Experience leading technical design for complex systems and guiding implementation across multiple engineers or teams
- Experience with relational and NoSQL databases, schema design, performance tuning, and data modeling
- Experience building and operating cloud-native systems using AWS, Docker, Kubernetes, and infrastructure as code
- Strong understanding of observability, reliability, and operational excellence in production environments
- Ability to work through ambiguity, decompose complex problems, and align engineering, product, and design stakeholders
- Demonstrated ability to improve engineering quality through standards, design reviews, mentoring, and reusable platform patterns
- Hands-on experience with AI-native development tools such as Cursor and Augment
- Ability to evaluate AI-generated code and outputs for failure modes, regressions, and edge cases
- Preferred experience with document processing pipelines, structured extraction, vector stores, MLOps tooling, experiment tracking, or model deployment pipelines
- Preferred background in financial document processing or fintech data pipelines
- Prior technical lead or TLM experience on a new or early-stage product team is preferred
Benefits
- Health, dental, and vision care for employees and families
- Life insurance
- Mental wellness coverage
- Fertility and growing family support
- Flexible time off and company-paid holidays
- Paid family, medical, and bereavement leave
- Retirement saving plans
- Allowance for home work and technology setup
- Annual professional development stipend
- Fully remote or office-based work options, with hybrid flexibility and offices in San Francisco, New York City, Mumbai, and Bangalore
Categories
About Juniper Square
Juniper Square builds software and provides fund administration for private markets general partners, including real estate, private equity, and venture firms. Its SaaS platform supports fundraising, investor onboarding, compliance, treasury, reporting, and LP communications, with optional administration services and applied-AI tools integrated into clients’ systems. Founded in 2014 and headquartered in San Francisco, it is privately held and used by more than 2,000 GPs worldwide.