engineering
Posted Apr 16Software Engineer - Developer Products (AI)
at Workato
San Francisco, United StatesOn-site
Responsibilities
- Design, build, and maintain robust, scalable, and high-quality developer-facing products and APIs for LLM and Agentic application development. •
- Collaborate closely with product managers, designers, developer relations and other engineers to translate developer needs and product
- Write clean, maintainable, and well-tested code, and contribute to a high standard of engineering excellence within the team. •
- Implement and improve validation, monitoring, and observability for ML services within the sandbox environment. •
- Drive the full development lifecycle : from ideation and architecture to deployment and continuous improvement. •
- Identify and resolve bottlenecks, bugs, and technical challenges in a fast-paced, iterative environment. •
- Conduct code reviews and mentor team members to uphold high engineering standards. •
Requirements
- Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform.
- With enterprise-grade security and continuous innovation at its core, Workato provides the trusted foundation for organizations to automate with confidence and operationalize AI across the business.
- You will be instrumental in shaping the future of how developers interact with and build on top of Workato's ecosystem in the age of AI.
- Stay at the cutting edge of AI, LLMs, and developer tooling, bringing new ideas and technologies to the team. Requirements Qualifications /
- Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or equivalent industry experience. • 3+ years of
- experience of professional software development experience, with a proven track record of shipping high-quality products. •
- You are proficient in one or more modern programming languages such as Go, Python, Ruby, or JavaScript and hands-on experience with LLM models. •
- Proven track record of deploying and maintaining ML services in production environments is a strong plus. •
- Solid understanding of API design, developer tooling , software architecture, data structures, and algorithms. • LLMops/MLops