The job, in the employer's words
Are you passionate about building highly accurate, calculation-intensive financial systems where correctness, scale, and transparency are critical? Do you enjoy solving complex quantitative challenges involving large datasets, financial calculations, and analytics infrastructure? Are you looking for an opportunity to help shape the next generation of investment performance and analytics technology?
Ridgeline is seeking a Senior Software Engineer to help scale our investment performance and analytics platform. This role sits at the intersection of software engineering, quantitative financial analytics, and investment technology. You will design and build sophisticated systems that power performance measurement, attribution, and reporting across complex investment portfolios.
The investment performance domain includes nuanced financial methodologies, complex asset behaviors, and institution-grade reporting requirements. Candidates who have worked on investment analytics or other quantitative financial platforms tend to ramp most successfully in this environment.
While experience with performance measurement systems is highly valuable, we recognize candidates may come from adjacent areas of investment technology. Engineers with experience in portfolio analytics, risk systems, portfolio accounting, market data, trading systems, or other quantitative financial platforms are encouraged to apply.
By joining Ridgeline, you'll help redefine investment management technology while working alongside a team committed to collaboration, learning, and technical excellence.
Our hybrid model is 3 days in office per week.
Relocation assistance is available for qualified candidates.
You must be authorized to work in the United States without sponsorship.
The Impact You Will Make
You'll play a key role in designing and evolving Ridgeline's investment performance and analytics platform, building systems that support sophisticated reporting workflows and help investment managers make informed decisions. Working in a fast-paced, collaborative environment, you'll partner closely with product, strategy, and engineering teams to design scalable solutions, drive technical decision-making, and influence the direction of a growing platform.
In this role, you'll contribute throughout the software development lifecycle, from requirements gathering and design reviews through implementation, testing, and deployment. You'll develop systems capable of supporting complex asset classes including fixed income, derivatives, private equity, and other alternative investments, while helping optimize critical calculations such as time-weighted returns (TWR), internal rates of return (IRR), and performance attribution methodologies.
You'll also help shape and enhance a modern technology stack built on AWS, creating automation and scalable solutions that customers rely on to run their businesses. As a staff engineer, you'll provide technical leadership, mentor fellow engineers, and help establish engineering best practices across the team. Success in this role requires creativity, strong problem-solving skills, and the ability to communicate complex ideas clearly while contributing to a culture rooted in collaboration, continuous learning, and transparency.
What We Look For
Core Engineering Experience
From a technical perspective, we're looking for someone with experience working with relational and analytical databases, including query optimization and data modeling, as well as experience building cloud-native applications on AWS, Azure, or Google Cloud. You should have a strong appreciation for automated testing, software quality, and maintainable system design, along with the ability to balance immediate business needs with long-term architectural thinking.
Financial Systems Experience
We're looking for an experienced software engineer with a strong background designing and building complex analytics, reporting, or financial systems. The ideal candidate brings experience developing software within investment management or other institutional financial environments and has worked on systems involving performance measurement, portfolio analytics, risk, portfolio accounting, market data, trading, or similar quantitative financial domains.
You should have a solid understanding of investment management concepts and experience working with complex financial instruments such as equities, fixed income, derivatives, or alternative investments. While not expressly required, familiarity with performance measurement methodologies, attribution concepts, profit and loss analysis, and investment reporting workflows is highly valued, as these domains require careful attention to accuracy, transparency, and financial correctness.
This role is particularly well suited for engineers who enjoy building highly accurate, calculation-intensive systems where data quality, scalability, and numerical precision are critical. The investment performance domain includes nuanced financial methodologies, complex asset behaviors, and institution-grade reporting requirements, so candidates who have worked on investment analytics or other quantitative financial platforms tend to ramp most successfully in this environment.
Preferred Experience
A degree in Finance, Computer Science, Information Science, or a related discipline is preferred. Familiarity with GIPS, Brinson Attribution, TWR, IRR, and other investment performance methodologies is highly desirable, as is experience with financial data providers such as Bloomberg, FactSet, Refinitiv, or ICE. CFA, CIPM, or related industry certifications are considered a plus, but are not required. Experience with Kotlin or other JVM languages and familiarity with modern AI-assisted development tools such as GitHub Copilot or ChatGPT are also beneficial.
About Ridgeline
Ridgeline is the first front-to-back system of record for investment managers. Founded by visionary entrepreneur Dave Duffield (co-founder of both PeopleSoft and Workday), the company was created to modernize an industry held back by outdated, disconnected technology. Powered by a single, real-time data set and embedded AI, Ridgeline helps firms automate complexity, accelerate collaboration, and deliver tailored client experiences at scale, without added headcount or risk. Ridgeline is headquartered in Lake Tahoe, with offices in New York, Reno, the Bay Area, Dublin Ireland. Ridgeline is recognized by Fast Company as a “Best Workplace for Innovators,” by Frost & Sullivan as a “Technology Innovation Leader,” and by The Software Report as a “Top 100 Software Company.
Ridgeline is proud to be a community-minded, discrimination-free equal opportunity workplace.
Ridgeline processes the information you submit in connection with your application in accordance with the Ridgeline Candidate Privacy Policy. Please review the Ridgeline Candidate Privacy Policy in full to understand our privacy practices and contact us with any questions.
This posting is for an existing vacancy.
Compensation and Benefits
The typical starting salary range for new hires in this role is $153,000 - $210,000. Final compensation amounts are determined by multiple factors, including candidate experience and expertise and may vary from the amount listed above.
As an employee at Ridgeline, you’ll have many opportunities for advancement in your career and can make a true impact on the product.
In addition to the base salary, Ridgeline employees can participate in our Company Stock Plan subject to the applicable Stock Option Agreement. We also offer rich benefits that reflect the kind of organization we want to be: one in which our employees feel valued and are inspired to bring their best selves to work. These include unlimited vacation, educational and wellness reimbursements, and $0 cost employee insurance plans. Please check out our Careers page for a more comprehensive overview of our perks and benefits.
Relocation assistance is available for qualified candidates.
#LI-Hybrid
Benefits mentioned
- The typical starting salary range for new hires in this role is $153,000 - $210,000. Final compensation amounts are determined by multiple factors, including candidate experience and expertise and may vary from the amount listed above.
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