Jobs at Ridgeline

Designs and strengthens identity and access management by implementing RBAC, managing account and permission inventories, automating provisioning and de-provisioning, conducting access audits, developing security policies, leading IAM-related incident response, and maintaining technical documentation. The role requires collaboration across security and IT teams to support compliance with NIST, GDPR, ISO 27001, and other identity management standards.

Secure AWS cloud environments through architecture and network reviews, IAM and policy guardrails, workload protection, monitoring, threat detection, encryption, runtime controls, and secure CI/CD automation. Develop scalable security tooling, including AI-augmented solutions, and establish secure integrations with third-party services. Partner with engineering, product, DevOps, and compliance teams through design reviews, code reviews, documentation, and technical guidance.

Leads frontend modernization for the Market Data team, including migrating the Instrument Master UI from legacy patterns. Defines frontend strategy, mentors engineers, establishes coding standards, improves testing and maintainability, and partners with product and backend teams on user needs, APIs, and data contracts.

Lead the design and implementation of enterprise AI learning and enablement programs at Ridgeline, fostering AI adoption across all employee levels.

Create and maintain user-focused product documentation (user guides, API references, in‑app guidance, release notes). Collaborate with product, engineering, and design to translate complex concepts into clear content using structured authoring (DITA/XML), CCMS, and AI-enabled tools. Improve content reuse, discoverability, and migration; apply accessibility and localization best practices; support scalable content operations and documentation standards.

The Senior Staff Total Rewards Partner will develop and manage total rewards strategies, including compensation, equity, and benefits, to support global growth and IPO readiness. This role involves partnering with multiple departments and shaping the company’s compensation philosophy and benefits strategy to attract and retain talent.

Build and evolve Ridgeline’s investment performance and analytics platform. Responsibilities include software design, implementation, requirements and design reviews, AWS backend development, developer automation, scalable application development, analytical data modeling, and query optimization across OLAP and columnar systems. The role involves complex investment analytics, collaboration across design and strategy teams, automated testing, problem solving, and continuous learning in a financial technology environment.

Build and ship full-stack features for Client Management: frontend (React/TypeScript), backend services (Java/Kotlin), APIs (REST/GraphQL), and SQL-backed data flows. Collaborate with product and design, participate across the SDLC, write tests and maintainable code, improve developer automation and observability, and use cloud-native patterns and AI tools to accelerate development.

Design, build, and support scalable cloud-native Trade Order Management applications. Participate across the SDLC, troubleshoot production incidents, improve system reliability, mentor engineers, and collaborate with product and design to deliver secure, high-performing trading workflows.

Build and maintain automations (Okta Workflows, Jira Automation, Atlassian Rovo) to deflect repetitive tickets; develop automation pipelines; scope sprint work; and provide hands-on Tier 1/2 in-office support including laptop provisioning, account lifecycle management, and Mac fleet administration using Jamf and Google Workspace.

Build and evolve Ridgeline's AI data platform: design secure API integrations and MCPs, implement RAG pipelines and vector database solutions, scale distributed systems, enforce data lineage/access controls, and mentor peers while shaping AI platform strategy.

Design and evolve extensible enterprise platform frameworks (search, audit, custom fields). Lead architecture for data models, APIs, event-driven workflows, indexing pipelines, and operational patterns. Drive scalable, secure, performant solutions, participate in on-call and production support, use AI tools responsibly across the SDLC, and mentor engineers while collaborating across product and platform teams.

Lead design and implementation of a next-generation performance and analytics platform. Build cloud-native services on AWS/Azure/GCP, optimize OLAP/columnar queries, model analytical data, enable large-scale analytics, and create developer automation and tests. Collaborate across design, strategy, and engineering to deliver scalable, production-grade solutions for investment performance and attribution reporting.

Lead architecture and execution of detection and response capabilities across AWS and broader infrastructure. Build AI-augmented detection/triage pipelines, design SIEM/SOAR ingestion and alerting frameworks, drive incident response for high-impact events, close detection gaps, mentor engineers, and set team standards for responsible AI usage.

Lead services sales for enterprise asset management software by scoping engagements, drafting and refining SOWs, shaping deal strategy, influencing pricing and contracts, translating requirements into delivery plans, and maintaining services pipeline and forecasting to scale consulting capacity.

Design and build a next-generation performance and analytics platform using OLAP/columnar technologies and cloud-native services. Work across the full software lifecycle to optimize analytical queries, implement developer automation and automated tests, and collaborate with design and strategy to deliver scalable, high-performance investment analytics.

Create and maintain scalable learning assets (videos, eLearning, guides, slide decks, microlearning) using AI and modern tools. Execute instructional designs, manage multiple projects, analyze learner feedback and metrics, ensure accessibility, and collaborate with cross-functional teams to improve learning outcomes.

The Software Engineer will design and build scalable backend systems and data platforms, developing data pipelines and migration tools while collaborating with cross-functional teams and managing ambiguous requirements.

Lead the design and architecture of large-scale reporting systems, mentor engineers, and drive technical initiatives. Collaborate across teams to enhance data accessibility and performance optimization.

Manage a portfolio of investment and wealth management customers to accelerate time-to-value, drive product adoption, and retain/expand revenue. Coordinate onboarding, execute account plans, run trainings/workshops, surface product feedback, and partner cross-functionally to remove adoption barriers. Use AI-enabled tools and CS platforms to monitor customer health, scale outcomes, and contribute to process improvements while supporting up to 25% domestic travel.