Senior AI Engineer (Agents)
About Workato Workato delivers enterprise infrastructure for the agentic era, redefining iPaaS and helping enterprises unify data, applications, processes, and AI into a single, governed platform. A leader in Enterprise MCP and trusted by 50% of the Fortune 500, Workato’s cloud-native architecture connects every application, data source, and process to power real-time orchestration at scale. 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. To learn more, visit www.workato.com Why join us? 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
Responsibilities
We are looking for an experienced and exceptional Senior AI Engineer (Agents) to join our growing team. In this role, you will be involved in the design, development, and optimization of AI and Machine Learning products that deliver exceptional user experiences. The ideal candidate will combine strong software engineering skills with deep knowledge of machine learning systems. As part of this role you will: Design and implement advanced AI/ML systems with a focus on LLMs, AI Agents, and retrieval-augmented generation (RAG) architectures. Build production-grade AI pipelines for data processing, model training, fine-tuning, and serving at scale. Build conversational AI interfaces that handle multi-turn customer interactions, maintain context across sessions, and seamlessly escalate to human agents when necessary. Implement feedback loops and continuous learning systems that incorporate customer satisfaction metrics, agent corrections, and conversation outcomes to improve model performance over time. Create analytics dashboards and reporting tools to track automation effectiveness, identify common customer pain points, and measure key performance indicators like resolution time, containment rate, and customer satisfaction scores. Lead technical initiatives for AI system integration into existing products and services. Collaborate with data scientists and ML researchers to implement and productionize new AI approaches and models.
Requirements
Qualifications / Experience / Technical Skills Bachelor's degree in Computer Science, or a related field, or equivalent practical experience. 5+ years in backend software development using modern programming languages (e.g., Python (strongly preferred!), Golang or Java). Demonstrated experience building production conversational AI systems including chatbots, virtual assistants, and automated support agents using LLMs (OpenAI, Anthropic, open-source models). Expertise in natural language understanding (NLU) and intent classification for customer query interpretation, entity extraction, and conversation flow management. Experience implementing multi-channel support automation across chat, email, voice, and messaging platforms with consistent context handling. Strong background in customer support metrics and KPIs including CSAT, first contact resolution, average handle time, and containment rate optimization. Experience with sentiment analysis and emotion detection for escalation triggers and customer satisfaction monitoring. Expertise in building knowledge bases and FAQ systems with dynamic content retrieval and self-learning capabilities from support interactions. Proficiency with contact center platforms (Zendesk, Salesforce Service Cloud, Genesys, or similar) and their API integrations. Experience implementing real-time agent assist systems that provide suggestions, knowledge articles, and response templates during live interactions. Familiarity with compliance and security requirements for handling sensitive customer data in automated systems (PCI, HIPAA, GDPR). Experience with A/B testing and experimentation frameworks for optimizing conversation flows and response strategies. Soft Skills / Personal Characteristics 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 search problems (REQ ID: 2456)