Embedded Software Engineer developing embedded and Lua software for ORBCOMM’s IoT Smart Tracking products. Building terminal applications, troubleshooting defects, and expanding automated testing.
About the role
- Principal Software Development Engineer overseeing Flowise AI platform architecture and leading technical decisions for scalable systems. Collaborating on open source and enterprise AI deployments.
Responsibilities
- Define and evolve the shared platform layer powering Flowise across open source, cloud, and enterprise deployments
- Design modular SDKs, runtime systems, and integration patterns that ensure portability, extensibility, and long term maintainability
- Own end-to-end system design including APIs, data models, service boundaries, and deployment strategies
- Lead architectural decisions for AI agent design patterns, LLM orchestration, RAG pipelines, evaluation frameworks, model routing, safety guardrails, and performance optimization
- Drive production reliability, observability, and cost efficiency strategies for AI workloads
- Define the roadmap for open source and enterprise, and design workflows that allow both codebases to evolve without creating maintenance debt
- Represent Flowise in cross organizational architectural discussions and influence standards for enterprise AI deployment within Workday
- Contribute directly to the TypeScript monorepo (Node.js, React, Express)
- Review pull requests, debug complex issues, and participate in production on call rotations
- Raise the bar on testing practices, CI/CD pipelines, and observability standards
- Mentor senior engineers and influence technical direction through design reviews and collaboration
Requirements
- 8+ years of software engineering experience building large scale production systems
- 6+ years of experience and expertise in JavaScript/TypeScript, Node.js, and React
- 6+ years of experience architecting distributed systems and scalable APIs
- Strong background in relational databases, cloud infrastructure (AWS preferred), and CI/CD tooling
- Track record of owning systems from requirements through production operations
- Experience building production AI systems (LLM applications, RAG pipelines, agent frameworks)
- Experience with MCP, LangChain, or similar orchestration frameworks
- Hands-on experience with Docker, Kubernetes, and Infrastructure as Code
- Experience with authentication protocols (OAuth, JWT, SSO)
- Experience with multi-tenant systems and embedding applications within host platforms
- Experience influencing architectural decisions across multiple teams or organizations
- Ability to clearly communicate complex architectural decisions to engineers, product leaders, and executive stakeholders
- Demonstrated ability to lead through influence rather than authority
Benefits
- Workday Bonus Plan
- Commission/bonus potential
- Annual refresh stock grants
- Flexible work arrangements
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