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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
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 experienced and exceptional Senior AI Engineer (Voice AI) 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. If building AI products from zero to one that scales to serve millions of users from first principles of AI and engineering, you are at the right place. We are building organization-aligned agents that are consistent at scale from the ground up and looking for passionate builders who are rooted in foundational AI knowledge to reimagine the agent control and data plane.
As part of this role you will:
Design and implement advanced AI/ML systems with a focus on SLMs, LLMs, AI Agents, and Search architectures.
Build conversational AI interfaces that handle multi-turn low latency chat/voice customer interactions, maintain context across sessions, and seamlessly escalate to human agents when necessary.
Build production-grade AI pipelines for data processing, model training, fine-tuning, benchmarking (dual-control, fluid model etc.) and serving at scale.
Implement feedback loops and continuous learning systems that incorporate customer satisfaction metrics, agent corrections, LLM evaluations, human evaluations and conversation outcomes to improve model performance over time. Reinforce organizational policies based on knowledge bases, conversational data and memory systems.
Create AI based analytics dashboards and reporting tools to track automation effectiveness, tracing for identifying bottlenecks, identify common customer pain points, and measure key performance indicators like resolution time, containment rate, and customer satisfaction scores. Quality assurance, management to get actionable insights from customer conversations and create evals for the current generation agents.
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.
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 AI systems including chatbots, virtual assistants, and automated support agents using SLMs, LLMs (commercial, open-source models).
Demonstrated strong foundational understanding and appreciate first principles thinking in ML, NLP (transformer based models).
Expertise in natural language understanding (NLU) and intent classification for customer query interpretation, entity extraction, dialogue state tracking and conversation flow management for building a reliable framework for context engineering.
Expertise in tuning streaming ASR and TTS engines, Speech to Speech models for context and domain aware transcriptions and naturalness in voice.
Expertise in conversation mining for identifying customer intents, root cause analysis, sentiment, resolution, policy adherence for not just auditing but truly understanding conversations for business outcomes across large enterprise scale.
Expertise in working with use case based SLMs for realtime agent coaching and recommendations.
Expertise in building knowledge bases and FAQ systems with dynamic content retrieval and self-learning capabilities from support interactions.
Experience implementing multi-channel support automation across chat, email, voice, and messaging platforms with consistent context handling.
Deep knowledge of REST API design, Pub-Sub architectures and integration patterns
Experience working with PostgreSQL and ClickHouse, or similar relational and analytical databases (added advantage but not necessary skill)
Strong understanding of software architecture, scalability, security, and system design.
Experience with Docker, Kubernetes, and deploying to cloud environments (AWS, GCP, or Azure) is a plus
Experience with A/B testing and experimentation frameworks.
Strong communication abilities to explain technical concepts
Collaborative mindset for cross-functional team work
Detail-oriented with a strong focus on quality
Self-motivated and able to work independently
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