Juniper Square

• Build the demand generation engine. Stand up the demand gen programs, plays, data, and tooling that connect to and fuel the rest of the unified pipeline team — events and field marketing, SDRs, and sales associates — so that target accounts keep progressing through every stage of their journey. • Make demand generation AI-native. Lead a demand motion built as a closed loop: agents research every target account, watch for trigger events like fund closes, executive moves, and competitor signals, and personalize outreach the moment a buying window opens. Channel-native creative is composed from canonical positioning, voice, and proof points rather than re-derived from scratch for each campaign, and spend reallocates on measured response so what works sharpens the next cycle. • Break the demand generation playbook. The firms we're after are a small, sophisticated audience that tunes out generic marketing. You’ll need to go beyond the tried-and-true channels every demand gen playbook reaches for and invent unconventional programs, formats, and moments that earn attention and trust with this audience. • Build and develop a high-performing, AI-fluent team. Hire, lead, and grow a team of campaign and channel marketers who work AI-first by default. Set clear ownership, coach for impact, and raise the bar on the quality and velocity of the work. • Operationalize account targeting and tiering. Partner with sales to sharpen the ideal customer profile, select and prioritize target accounts, and align on shared goals and account priorities. • Orchestrate across the motion. Build a tight operating rhythm with the outbound and field teams you sit alongside, so that targeting, account status, and next steps stay shared and the full motion moves accounts forward together. • Own the number. Be accountable for the pipeline your programs create, and define and report on the metrics that matter — account progression, pipeline created, and win rate. • Own the budget. Allocate ABM and channel spend, including agency investment, to the highest-return programs.

• Ingest and structure historical data and documents into Juniper Square platforms, ensuring information is accurately captured and properly organized for use within AI-assisted workflows. • Receive and process incoming work requests within defined SLAs, working within AI-powered workflows to move requests efficiently from intake to completion. • Review AI-generated outputs for accuracy, completeness, and alignment with source material, applying consistent judgment at every step before work is considered complete. • Follow established operating procedures with precision, and actively contribute to refining and improving them. • Partner closely with customer-facing teams, maintaining clear communication and reliable turnaround accountability across multiple product workflows. • Serve as an operational point of contact for both internal stakeholders and external customers, representing Juniper Square with professionalism and clarity.

• Manage a portfolio of 60-75 existing customer accounts • Work with end-users of the product on implementation, onboarding, product adoption, and renewals • Review customer metrics for product adoption, client satisfaction, and customer goals • Develop advanced knowledge of the customer, product, and industry • Contribute to internal projects that improve operational infrastructure • Work with product and engineering teams to create new product features that reflect the voice of our customers • Use AI tools (e.g., Claude) as part of your core CSM workflow so you arrive sharper, faster, and more customer-ready. • Look for ways to apply AI across your book and your own workflow, and share what works so the wider team benefits.

• Analyze and map data fields from source systems to target system requirements. • Identify and correct data inconsistencies, errors, and duplicates to ensure data quality. • Perform data validation checks to verify data accuracy and completeness. • Transform data into specified formats and structures as required. • Maintain clear and accurate documentation of data conversion processes and findings. • Troubleshoot data conversion issues and propose solutions. • Work closely with the Product Onboarding Manager and other team members to achieve project goals.

Role Description We are looking for a highly experienced and autonomous Group Product Manager to own our newest product (Dex), an intelligent AI-native data warehouse for private markets. This is a flagship zero-to-one role where you will: - Define the vision and multi-year strategy for one of the most consequential product areas at Juniper Square. - Operate as the lead product voice and drive the data foundation that powers both our external products and our internal fund administration operations. - Transform fragmented, document-heavy private markets data into a clean, structured, trustworthy foundation. - Own the entire pipeline and define how this product serves as the data backbone for Juniper Square’s apps, AI agents, and managed services. AI fluency is a baseline expectation. PMs at this level should be comfortable using the full range of modern tools (e.g. LLMs, Cursor, Claude) to: - Orchestrate AI agents to synthesize customer feedback into working hypotheses. - Build functional prototypes before writing requirements. - Use coding agents to submit pull requests for engineering. This role would benefit from in-person collaboration in San Francisco, although we also welcome exceptional candidates from elsewhere in the United States and Canada. What you’ll do - Own the vision, strategy, and roadmap: Define the multi-year vision and strategy for Dex as both an external product and the internal backbone for Juniper Square’s fund administration operations. Sequence the roadmap optimally for Dex to scale across new use cases and customer profiles. - Talk to customers: Spend meaningful time with the GPs who depend on clean, aggregated data, as well as with our internal fund administration team. Use customer insights to challenge and ultimately sharpen strategic direction. - Lead cross-functionally: Partner with engineering, design, fund administration, customer success, sales, forward-deployed AI development teams, and executive stakeholders to align on strategy and ensure execution serves both the business and the customer. - Ship end-to-end: Take problems from discovery through delivery. Plan projects, define requirements, and motivate those building solutions with an understanding of the "why" and the "what" to inspire their ownership of the "how." - Harness the power of AI: Own the product direction for AI-powered capabilities across the pipeline - agentic document ingestion, automated classification and extraction, intelligent mapping and enrichment, human-in-the-loop review, search and retrieval, and AI-driven data insights. - Simplify complexity: Take on the hardest problems in the domain and deliver solutions that feel simple. - Be a leader: Set direction across multiple workstreams and engineering teams. Provide mentorship and product leadership to other PMs working in and adjacent to the domain. Qualifications - 10+ years of product management experience in B2B or Enterprise SaaS, with a significant portfolio of shipped work across the full development lifecycle. - Proven experience owning a complex product area end-to-end, ideally in a zero-to-one context. - Background in data warehousing, data modeling, document ingestion and extraction, ETL/ELT pipelines, data quality and validation. - Experience building agentic workflows or production LLM features with real evaluation and monitoring discipline. - Fluency with LLMs and common AI tools (e.g. Claude, Cursor). - Strong communication skills, written and verbal, with the ability to articulate product decisions clearly. - Track record of leading through influence and setting strategy that multiple teams execute against. Compensation Compensation for this position includes a base salary, equity, and a variety of benefits. The base salary range for this role is $230,000 - $270,000 USD. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location. Benefits - 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.

• As a Principal Engineer, you will drive the team’s technical direction and play a pivotal role in designing and architecting accounting software systems. • This role involves mentoring team members, solving complex technical challenges, and delivering hands on contributions as a full stack leader. • You will work closely with engineers and cross functional partners across Product, Design, and Quality Assurance to expand system capabilities. • Your leadership will be instrumental in achieving the team’s objectives and advancing our technical vision. • Set the technical direction for AI systems, including shared AI SDKs, guardrails, evaluation frameworks, feedback systems, and agentic workflow infrastructure • Own architecture and technical strategy for complex backend and AI platform systems, from design through production • Lead technical design for ambiguous, cross functional initiatives, evaluating tradeoffs, aligning stakeholders, and driving implementation • Write production code as a hands on individual contributor, this is not a role that delegates implementation to others • Design and operate LLM powered systems, including RAG pipelines, agentic workflows, evaluation infrastructure, guardrails, and model observability.

• Set the technical direction for AI systems, including shared AI SDKs, guardrails, evaluation frameworks, feedback systems, and agentic workflow infrastructure • Own architecture and technical strategy for complex backend and AI platform systems, from design through production • Lead technical design for ambiguous, cross functional initiatives, evaluating tradeoffs, aligning stakeholders, and driving implementation • Write production code as a hands on individual contributor, this is not a role that delegates implementation to others • Design and operate LLM powered systems, including RAG pipelines, agentic workflows, evaluation infrastructure, guardrails, and model observability • Own end to end reliability of AI systems, from design through structured output delivery • Define quality benchmarks • Champion and embed AI native development practices and tools, such as Cursor and Augment, to drive meaningful productivity gains across the team • Foster a culture of rapid iteration, high velocity, and quality, including guiding the effective use of AI code generation • Mentor engineers, raise the quality of technical decision making, and help the team execute with consistency • Establish coding standards, review practices, and architectural documentation that scale as the team grows • Partner with recruiting to build and grow the team • Work closely with Engineering Managers, Product, Design, and QA to translate requirements into executable technical plans • Participate actively in design reviews and roadmap discussions with a grounded, implementation level perspective • Handle most cross team conflicts and technical decisions autonomously.

• Produce work in whatever form best serves the team and engineering, whether that's annotated flows, coded prototypes, LLM-generated specs with design system context loaded, or Figma files when a polished developer reference is needed. When handing off to engineering, ensure files are complete, accurate, and consistent with our design system. • Take on hard problems in your product domain and deliver solutions that feel simple. Our users work with sophisticated financial data and workflows. The complexity lives in the craft, not the interface. • Contribute to the UX of AI-powered capabilities across our product suite, including proactive recommendations, generative summaries, and predictive insights. Get the trust and transparency details right so these features feel reliable to enterprise customers, not like a black box. • Conduct research and interpret product analytics to uncover real user needs and measure the impact of your designs. Talk directly with customers, run quick tests, and treat research as a velocity tool rather than a gate. • Partner with product managers, engineers, and stakeholders to align on strategy and ensure design execution serves both the business and the user. Own the design relationship with your product area end to end. • Continuously improve and expand our design system, advocating for consistency and pattern reuse across the product suite. Collaborate with peers on the design team to give and receive feedback, raising the collective craft of the organization.

Role Description As a Technical Lead , you will drive the team’s technical direction and play a pivotal role in designing and architecting accounting software systems. This role involves mentoring team members, solving complex technical challenges, and delivering hands-on contributions as a full stack leader. You will work closely with engineers and cross-functional partners across Product , Design , and Quality Assurance to expand system capabilities. Your leadership will be instrumental in achieving the team’s objectives and advancing our technical vision. What You'll Do - Own Technical Direction and Architecture - Set the technical direction for AI systems, including shared AI SDKs, guardrails, evaluation frameworks, feedback systems, and agentic workflow infrastructure. - Own architecture and technical strategy for complex backend and AI platform systems, from design through production. - Lead technical design for ambiguous, cross-functional initiatives, evaluating tradeoffs, aligning stakeholders, and driving implementation. - Evaluate and select technologies with a bias toward what ships well and scales sustainably. - Build and Operate AI Systems - Write production code as a hands-on individual contributor; this is not a role that delegates implementation to others. - Design and operate LLM powered systems, including RAG pipelines, agentic workflows, evaluation infrastructure, guardrails, and model observability. - Own end-to-end reliability of AI systems, from design through structured output delivery. - Define quality benchmarks. - Champion AI Native Development - Champion and embed AI native development practices and tools, such as Cursor and Augment, to drive meaningful productivity gains across the team. - Foster a culture of rapid iteration, high velocity, and quality, including guiding the effective use of AI code generation. - Bring strong, informed opinions on how to get the most from AI assisted development while maintaining reliability and correctness. - Lead and Grow the Team - Mentor engineers, raise the quality of technical decision making, and help the team execute with consistency. - Establish coding standards, review practices, and architectural documentation that scale as the team grows. - Help define what “good” looks like for a team building at speed without sacrificing quality. - Partner with recruiting to build and grow the team. - Collaborate Cross Functionally - Work closely with Engineering Managers, Product, Design, and QA to translate requirements into executable technical plans. - Participate actively in design reviews and roadmap discussions with a grounded, implementation level perspective. - Handle most cross-team conflicts and technical decisions autonomously. - AI Fluency - Ability to critically evaluate AI generated code and outputs, including identifying failure modes, regressions, and edge cases introduced by AI assisted development. - Experience building and shipping production grade software using AI assisted workflows across the full SDLC. - Hands-on experience developing or integrating LLM powered systems, such as agents, copilots, tool using workflows, or multi-step reasoning systems. - Familiarity with patterns such as tool calling agents, planning and execution loops, and retrieval augmented generation (RAG). - Demonstrated ability to leverage modern AI tools to improve development velocity, code quality, and problem solving. - Experience contributing to AI powered features, such as intelligent search, conversational interfaces, recommendations, and automation. - Working knowledge of LLMs, embeddings, semantic search, and RAG pipelines. - Ability to identify and evaluate opportunities to integrate AI capabilities into products and workflows. Qualifications - Bachelor’s degree in Computer Science or equivalent work experience. - 7 to 10 years of experience in software development across building, integration, security, and architecture. - Previous experience building enterprise grade APIs is a plus. - Previous experience leading a team is a plus. - Expertise in object oriented programming with Python as the primary language. - Experience with front end technologies such as React, CSS frameworks, HTML, and JavaScript. - Experience with relational databases such as Postgres and MySQL. - Experience with SQL database schema design and query optimisation. - Experience with cloud technologies, preferably AWS, and container technologies such as Docker and Kubernetes. - Experience with GraphQL and Apollo Server is a plus, but not required. - You must be flexible and adaptable, and comfortable operating in a fast paced startup environment. Benefits - Variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. - Investment in digital-first operations, allowing effective collaboration across multiple locations. - Physical offices in San Francisco, New York City, Mumbai, and Bangalore for employees who prefer to work in an office.

• Own end-to-end accountability for Investor Services delivery across a portfolio of the firm's largest and most complex client relationships, including major enterprise engagements requiring white-glove coordination and executive-level partnership. • Lead, develop, and hold accountable a team of Directors and their globally distributed organizations spanning investor onboarding, AML compliance, treasury operations, CRM administration, and investor portal delivery. • Design and execute the organizational structure, staffing model, and capability roadmap required to absorb significant new business volume without sacrificing service quality or team health. • Build and maintain a rigorous quality assurance framework across Investor Services — defining standards, audit mechanisms, and feedback loops that give leadership visibility into operational health and give clients confidence in our execution. • Own the strategic relationship with key enterprise clients, serving as an executive escalation point and a proactive thought partner on how Juniper Square can better serve their evolving needs. • Drive cross-functional alignment with Product, Fund Accounting, Customer Success, Sales, and Compliance to ensure the operating model keeps pace with platform development and market commitments. • Lead workforce planning across a large, globally distributed organization — including headcount modeling, geographic footprint decisions, and succession planning for critical leadership roles. • Establish and own the KPI framework for Investor Services, translating operational data into insights that inform resourcing decisions, client conversations, and strategic planning at the executive level. • Identify and lead initiatives to improve automation, workflow efficiency, and controls — especially in high-volume, high-stakes areas like LP onboarding and capital event processing. • Represent Investor Services in firm-wide strategic discussions, contributing operational perspective and market intelligence to product, go-to-market, and leadership planning.