What You'll Do
As an AI Platform Software Developer, you'll work alongside our Architecture, Development and Product teams to help define and deliver the next generation of intelligent capabilities across the Curve platform.
This is a hands-on engineering role. You'll spend the majority of your time designing, building, reviewing, and delivering production software while helping guide the technical direction of AI across the organization.
Your responsibilities will include:
- Partnering with the Architecture team to evolve Curve's AI platform and establish development standards, reusable frameworks, and development patterns that enable teams to build intelligent applications at scale.
- Collaborating on the technical design, development, testing, and delivery of production services, agentic workflows, MCP servers, machine learning capabilities, and shared platform components.
- Writing high-quality production code while leveraging modern AI-assisted development tools, including Claude Code, to improve engineering productivity and software quality.
- Working side-by-side with developers, product managers, and UX designers to transform business requirements into secure, scalable, maintainable production software
- Performing technical design reviews, performing code reviews, mentoring developers, and contributing hands-on throughout the entire software development lifecycle
- Solving complex development challenges involving distributed systems, intelligent workflows, APIs, cloud-native services, and modern AI technologies
- Continuously evaluating emerging AI technologies, frameworks, and development practices, bringing practical ideas that improve both our products and the way we build them
- Partnering with internal development teams and external partners to build, extend, and continuously evolve Curve's AI platform
- Taking ownership of production software by helping troubleshoot complex issues, improving reliability, and ensuring our AI capabilities meet the high standards our customers expect
What We're Looking ForWe're looking for an exceptional software developer who combines deep hands-on AI expertise with a passion for building production systems.
Required Qualifications- 8+ years of professional software development experience building scalable SaaS applications
- 3+ years designing, building, and deploying production AI applications, platforms, or intelligent workflow solutions
- Demonstrated experience taking AI solutions from proof-of-concept through production deployment and continuously improving them through evaluation, monitoring, iteration, and operational feedback
- Demonstrated experience writing high-quality production code and delivering software that customers rely on every day
- Strong expertise in modern backend development, with experience in Python or similar technologies
- Experience building or extending agentic AI systems, MCP servers or similar integration frameworks, machine learning solutions, and LLM based applications
- Strong understanding of distributed systems, APIs, cloud-native architectures and modern software development practices
- Experience participating in technical architecture discussions and collaborating across development teams to solve complex technical challenges
- Passion for mentoring developers through technical design, code reviews, pair programming, and hands-on collaboration
- Experience supporting and operating production software, including troubleshooting complex issues and driving problems through resolution
- Experience using AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot, or similar technologies with a desire to continually improve productivity and quality
- Thrives in a fast-paced environment, embraces ownership, and enjoys tackling difficult technical challenges wherever they arise
Preferred QualificationsExperience with one or more of the following:
- Production AI platforms (LangGraph, Amazon Bedrock, OpenAI, Anthropic, or similar technologies)
- Agentic AI frameworks and MCP servers, and AI integration ecosystems
- Retrieval-Augmented Generation (RAG), vector databases, and semantic search
- Production AI operations, including model deployment, evaluation, observability, governance, or MLOps
- Conversational AI, speech technologies or customer facing AI applications
- Building AI capabilities within large-scale, multi-tenant SaaS platforms
- Experience building software in healthcare or other highly regulated environments
