Senior Software Engineer, Agent Foundry

Ridgeline•Reno, NV

7d•Hybrid

About The Position

Are you passionate about building intelligent software systems that leverage large language models to solve complex business problems? Do you enjoy designing scalable backend platforms and full-stack experiences that bring AI-powered workflows into production? Are you excited to solve complex challenges involving agent orchestration, reliability, observability, and automation while helping shape the future of enterprise software? If so, we invite you to be a part of our innovative team. As a Senior Software Engineer, you'll help shape the future of AI-powered workflows across Ridgeline's platform. You'll build foundational services, frameworks, and integrations that enable intelligent agents to automate work, assist users, and unlock new capabilities across our products. Working closely with engineers, product managers, and AI platform specialists, you'll design and develop scalable systems that directly impact our clients and influence the future direction of the business. Our team of engineers are building with cutting-edge technologies—like Claude Code and Cursor—in a fast-moving, creative, progressive work environment. At Ridgeline, how we work matters as much as what we build. Ridgeliners act like owners, choose growth over comfort, and communicate with transparency. We assume positive intent, bias toward action, and bring solutions—not just problems. We celebrate wins, learn from setbacks, and thrive in a resilient, collaborative, high-performing culture. If the Ridgeline Way excites you, we’d love to meet you. You must be work authorized in the United States without the need for employer sponsorship.

Requirements

5+ years of professional software engineering experience building distributed systems, backend services, or platform infrastructure
Experience working with AI/ML technologies, large language models, or generative AI applications
Familiarity with prompt engineering, agent frameworks, retrieval systems, and AI evaluation techniques
Strong proficiency in Java, Kotlin, or similar backend programming languages
Experience designing and operating scalable, cost-efficient cloud-native applications
Experience or strong interest in full-stack development, including frontend technologies such as React and TypeScript
Deep understanding of APIs, service-oriented architectures, event-driven systems, and distributed computing
Strong software engineering fundamentals, including testing, observability, performance optimization, and system design
Ability to navigate ambiguity and move quickly from experimentation to production-ready solutions
Excellent communication and collaboration skills
Curiosity and enthusiasm for rapidly evolving AI technologies and their practical applications
Willingness to learn about cutting-edge technologies while cultivating expertise in a business domain and problem space
An aptitude for problem solving
Ability to communicate effectively
Serious interest in having fun at work

Nice To Haves

Experience building production applications using OpenAI, Anthropic, Gemini, or other foundation models
Experience with MCP (Model Context Protocol), tool calling, function execution, or agent orchestration frameworks
Experience designing developer platforms, frameworks, or internal tooling
Familiarity with AI evaluation methodologies, benchmarking, and observability platforms
Experience working within fintech, enterprise SaaS, or highly regulated environments
Contributions to open-source AI or developer tooling projects

Responsibilities

Design and develop scalable full-stack services that power AI agents across the Ridgeline platform
Build integrations with leading AI providers, including OpenAI and Anthropic
Develop agent orchestration frameworks, tool execution systems, and context management services
Improve evaluation frameworks that measure agent quality, reliability, safety, and performance
Create observability, monitoring, and debugging tools for AI-powered workflows and autonomous systems
Collaborate with product and engineering teams to identify high-impact opportunities for intelligent automation
Optimize platform performance, scalability, cost efficiency, security, and operational excellence for production AI workloads
Prototype and evaluate emerging AI technologies, frameworks, and architectural patterns
Contribute to technical design discussions and establish best practices for agent development across the company
Think creatively, own problems, seek solutions, and communicate clearly along the way
Contribute to a collaborative environment rooted in learning, teaching, and transparency