Ridgeline Logo

Ridgeline

Principal Engineer, AI Platform

Reposted Yesterday
In-Office or Remote
Hiring Remotely in San Ramon, CA, USA
253K-348K Annually
Expert/Leader
In-Office or Remote
Hiring Remotely in San Ramon, CA, USA
253K-348K Annually
Expert/Leader
Leads architecture and development of a production agentic AI platform. Defines technical strategy, engineering standards, reliability and model evaluation practices, and scalable AI capabilities. Designs RAG integrations, third-party data connections, model routing, tool use, and code execution systems. Partners across Engineering, Product, and Data to drive adoption, resolve technical challenges, and align AI investments with customer outcomes while contributing directly to product delivery.
The summary above was generated by AI

Are you a technical leader who thrives at architecting agentic AI systems and shipping them in production? Do you want to help define how autonomous, tool-using AI agents get built into a real, customer-facing product? If so, we invite you to apply to join our AI Platform team, where we're building the future of investment management software.

As a Principal Engineer on the AI Platform team, you will guide the architecture and development of Ridgeline's agentic AI platform while also directly contributing to product delivery. You'll help drive the design of the agentic systems, workflows, and capabilities that power our product, including how those agents access external data and use models efficiently, all in close partnership with the engineers who built the platform's foundation. This role offers broad, cross-company impact, working across teams throughout the firm to shape how AI capabilities are built and adopted, in a collaborative, high-agency team culture.

What will you do?
  • Define and drive technical strategy and architecture for Ridgeline's AI platform and shared AI capabilities across the company.
  • Lead technical decisions that enable engineering teams across the firm to use AI platform capabilities in scalable, reliable, secure, and responsible ways.
  • Identify and resolve systemic technical obstacles that limit the availability, usability, extensibility, or reliability of the AI platform, including proactively engaging teams building one-off AI solutions to bring them onto the shared platform.
  • Establish engineering standards and architectural approaches that help teams make sound decisions as AI technologies and capabilities evolve, including reliability and evaluation standards for AI models in production.
  • Partner across Engineering, Product, Data, and other functions to connect AI platform investments to company priorities and customer outcomes, adapting your working style to collaborate with diverse engineering squads.
  • Architect solutions for integrating external data via retrieval-augmented generation, including connections to third-party data stores, and build systems for token-efficient AI usage such as model routing and code execution.
  • Propose and evaluate new AI features to advance the platform's capabilities, and resolve technical debates to align teams around the right approach.
Desired Skills and Experience
  • 15+ years of software engineering experience, with deep expertise in systems architecture.
  • Significant experience building and shipping an AI-powered product in production, including agentic loop design, structured responses, tool calling, Model Context Protocol (MCP), and retrieval-augmented generation (RAG).
  • Proven ability to design scalable, efficient system architectures and evaluate the right technologies for AI system components.
  • Experience establishing software development best practices and reliability/evaluation standards for AI models in production.
  • Full-stack experience across front-end and back-end AI product development; proficiency in Kotlin, TypeScript, and React.
  • Experience working with both Anthropic and/or OpenAI models and APIs.
  • Track record of driving technical or architectural decisions and aligning stakeholders across teams, especially amid competing viewpoints.
  • Demonstrated success integrating third-party data sources and delivering measurable improvements in AI model performance and token efficiency in production.
Bonus
  • Experience with multi-agent systems, AI agent orchestration, or advanced model evaluation techniques.
  • Background in financial services or investment management.
  • Contributions to open-source AI/ML projects or publications in the space.
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 listed below.  In select locations (including, the San Francisco Bay Area, CA, and the New York City Metro Area), an alternate range may apply as specified below. 

The typical starting salary range for this role is: $253,000-$316,000. 

The typical starting salary range for this role in the select locations listed above is: $278,000-$347,500.

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.


#LI-Remote

Ridgeline San Ramon, California, USA Office

San Ramon, United States

Similar Jobs

One Month Ago
Remote or Hybrid
United States
Expert/Leader
Expert/Leader
Software
Own the technical vision and architecture for an AI platform of agents, skills, and tools. Scale retrieval/knowledge systems, build developer experience, orchestration, observability, and evaluation/feedback loops. Align cross-division engineering strategy and drive platform adoption.
Top Skills: APIsBraintrustData PipelinesEmbeddingsKnowledge GraphsLangfuseLanggraphLangsmithLlamaindexLlmsMcpMulti-Agent OrchestrationObservability PlatformsPythonRag PipelinesRetrieval SystemsVector Databases
26 Days Ago
Remote or Hybrid
USA
195K-290K Annually
Senior level
195K-290K Annually
Senior level
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Lead design, build, and deploy of large-scale data platforms for LLMs, RAG, and agentic AI systems. Hands-on coding, architecting fault-tolerant pipelines, establishing MLOps/DataOps best practices, mentoring engineers, and operationalizing research into production across Exabyte-scale distributed systems.
Top Skills: AirflowAWSBigQueryDaskDevsecopsDockerFlinkGCPGoJvmKafkaKubeflowKubernetesLangchainLlamaindexLlmsMlflowOciPulsarPythonRetrieval-Augmented Generation (Rag)RustSagemakerSnowflakeSparkVertex Ai
14 Days Ago
Remote
US
190K-235K Annually
Senior level
190K-235K Annually
Senior level
Healthtech
Build and lead a greenfield cloud platform supporting application, data, and AI workloads. Responsibilities include managing Terraform infrastructure, production EKS clusters, Helm deployments, CI/CD pipelines, security controls, observability, cloud cost allocation, and developer golden paths. The role establishes engineering standards, supports regulated-data compliance, partners across engineering teams, reviews infrastructure changes, mentors engineers, and writes production code while ensuring reliable, secure, and cost-effective service delivery.
Top Skills: AirflowAmazon EksAWSAws Secrets ManagerC#/.NetContainer RegistriesDagsterDatadogDnsDockerExternal SecretsGithub ActionsGitopsGoGrafanaHelmIamKafkaKubernetesLinux ShellOpentelemetryPrometheusPythonSparkTerraformVpc

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account