Jobs at Solovis

Serve as a trusted advisor to institutional investor clients, managing retention, renewals, account growth, downsell mitigation, contract transitions, and client value realization. Partner with internal teams to deliver solutions and maintain strong client experiences. The role requires institutional investment knowledge, relationship management, negotiation, risk assessment, analytics-informed account strategy, and ownership of revenue outcomes across a book of business.

Leads sales strategy and execution, owning new business bookings, ARR growth, enterprise renewals, retention, expansion, forecasting, deal execution, quota attainment, pipeline coverage, conversion rates, and sales productivity. The role requires building a repeatable sales motion, coaching and enabling teams, negotiating with senior stakeholders, developing strategic relationships, and using data-driven insights to improve performance.

Lead the cloud hosting strategy and operations to ensure 99.9% uptime, optimize cloud costs, enforce scalability and security standards (ISO 27001), maintain disaster recovery and business continuity, partner with product teams, and mentor cloud engineers to improve operational discipline and service quality.

Manage a team delivering data extraction, integration, enrichment, and QA for investment assets. Build and maintain automation (Alteryx, Power Automate, Python), manage APIs and data feeds, track KPIs/SLAs, recruit and cross-train staff, partner with cross-functional teams, and drive process improvements to reduce errors and increase automation coverage.

Lead a team delivering investment data through SLA-driven pipelines; design and maintain automation, manage data feeds/API integrations, perform extraction/mapping/enrichment and QA, track KPIs, recruit and cross-train staff, and drive process improvements using AI and automation to increase throughput and reliability.

Manage a team responsible for data ingestion, extraction, mapping, enrichment, QA/QC, and automation. Build and maintain Alteryx/Power Automate/Python workflows, manage APIs and feeds, track KPIs/SLAs, recruit and cross-train staff, and drive process improvements across public, private, and operational asset classes while partnering with cross-functional teams.

Lead and grow a data engineering team; define architecture and standards for ETL/ELT pipelines; hands-on design, code review, and development; ensure production reliability, monitoring, and incident response; partner with product and engineering on data roadmap.

Serve as the primary post-implementation technical partner for assigned institutional clients, ensuring data completeness, governance, and timely reporting. Support reporting cycles, advise on complex structures, surface client feedback to Product/Data, lead portfolio reclassification and special projects, and drive renewals and upsell opportunities while coordinating across Services, Support, Sales, and Product.

Lead Revenue Operations to drive revenue predictability and GTM productivity. Own planning, forecasting, territory design, KPI reporting, compensation/quota design, and sales enablement. Partner with GTM leadership and present strategic recommendations to executive leadership while also working hands-on with forecasting models and operational processes.

Configure and deploy Solovis software for institutional clients, gather requirements, design solutions, manage projects to time and budget, deliver client training, maintain billable utilization, and ensure high customer satisfaction through proactive problem solving and data-driven decisions.

Develop test plans and execute testing (including automation), collaborate with developers, report findings to improve product quality and accelerate delivery of the platform suite.

Senior Java engineer delivering AI-augmented production features and modernizations across a Java/Python/AWS stack. Pair with engineers to embed agentic practices, own systems end-to-end, participate in AI-augmented reviews, and judge agent use versus human intervention.

Senior Java engineer delivering AI-augmented production features and modernizations across a Java/Python/AWS stack. Own systems end-to-end, pair with engineers to transfer agentic practices, perform AI-augmented code reviews, and judge when to trust or intervene with agent outputs.

Serve as the sole HR representative for Philippines employees, ensuring local compliance, managing end-to-end onboarding, administering Dayforce HRIS, coordinating benefits and payroll activities, supporting M&A integrations and data migrations, and contributing to policy, performance management, and engagement initiatives under the Director of HR.

Lead end-to-end delivery of strategic AI initiatives, drive AI adoption across teams, coordinate cross-functional stakeholders, apply data to measure success, and prioritize the AI project portfolio with leadership.

Hunt and close complex B2B enterprise SaaS deals in a defined territory. Build pipeline through outbound prospecting, run full sales cycles, engage C-suite buyers, use value-based frameworks, maintain CRM accuracy, and travel ~25%.

Design, build, and maintain scalable ETL/ELT data pipelines and backend services. Implement data validation, monitoring, performance optimizations, CI/CD, and operational support while partnering with product and business stakeholders.

Design, develop, test, and deploy scalable enterprise software. Collaborate with product and development teams using agile practices, meet sprint and release targets, reduce escaped defects, write unit tests, and produce clear documentation to ensure high-quality, reliable releases.

Manage end-to-end fund manager data collection and documentation for institutional clients. Liaise with clients and fund managers, track outreach and timelines, ensure data accuracy and completeness, reduce manual overhead with tools, and maintain throughput and quality across high-volume reporting cycles.

Lead and deliver agentic AI initiatives across engineering, defining KPI frameworks, driving agentic workflow adoption, modernizing brownfield systems, planning capacity and budget, aligning stakeholders, and managing performance for AI proficiency.