Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility.
Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com.
Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley, please submit an application. We look forward to getting to know you!
Also, feel free to check out why:
Business Insider named us an “enterprise startup to bet your career on”
Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
Quartz ranked us the #1 best company for remote workers
We are looking for an exceptional Senior Backend Software Developer to join our growing team. Your primary focus will be on developing and maintaining systems powering sophisticated AI agents and generative AI applications. While the core of the role is backend development, experience with full stack technologies will be a plus. As part of this role you will:
Design and implement scalable backend systems that integrate effectively with AI services and components.
Develop robust APIs and middleware connecting SAAS platforms with AI capabilities.
Create and optimize data pipelines for efficiently collecting, transforming, and feeding information to AI models.
Monitor and improve system performance with specific focus on AI service integration points and response times.
Make architecture decisions for AI integration projects, including technology selection and build vs. buy evaluations.
Collaborate with data scientists and ML engineers to understand model requirements and implementation needs.
Lead AI-related technical initiatives including mentoring junior engineers on AI integration patterns.
Implement comprehensive testing and monitoring strategies for AI-integrated systems to ensure reliability.
Ensure security and compliance in AI implementations, particularly regarding data handling and privacy regulations.
Communicate technical concepts to stakeholders and translate business requirements into effective AI solutions.
Bachelor's degree or above in Computer Science, related field, or equivalent practical experience. We value both traditional education and self-taught expertise.
5+ years in backend development using modern programming languages (e.g., Python, Java) with demonstrated experience building production systems.
Proven experience with cloud platforms (AWS, Azure, GCP), particularly their AI/ML services and infrastructure components.
Expertise in API development and management, including RESTful APIs, GraphQL, and API gateways for AI service integration.
Advanced database knowledge with both SQL and NoSQL databases, including data modeling for AI applications.
Experience integrating or implementing AI/ML services such as NLP, document processing, classification systems, or recommendation engines.
Proficiency with containerization and orchestration (Docker, Kubernetes) for deploying scalable AI-enabled applications.
Experience with message queues and event-driven architectures (Kafka, RabbitMQ) for handling asynchronous AI workloads.
Familiarity with any search engine technology is a plus (Elasticsearch, Solr, or similar).
Demonstrated ability to design and implement data pipelines that efficiently prepare and process data for AI consumption.
Knowledge of security best practices for AI systems, including data encryption, secure API design, and authentication mechanisms.
Experience with monitoring, logging, and observability tools for tracking AI system performance and troubleshooting issues.
Familiarity with CI/CD pipelines for reliable deployment of AI-integrated applications.
Strong communication abilities to explain technical concepts
Collaborative mindset for cross-functional team work
Detail-oriented with strong focus on quality
Self-motivated and able to work independently
Passion for solving complex problems