Staff AI Engineer

Навыки

• AI-агенты
• API (интеграции)
• ArgoCD / Flux
• CI/CD
• Коммуникация
• Решения на данных
• Распределённые системы

О компании и продукте

• 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!

Задачи

• We are looking for a Staff AI Engineer to play a key role in building the core of our AI platform
• In this position, you will design and develop production-grade systems that power intelligent automation, agentic workflows, and large-scale retrieval services
• This is a highly technical, hands-on role that involves close collaboration with product and platform teams to transform advanced AI concepts into reliable, scalable, and secure solutions used across our enterprise ecosystem
• You will also be responsible to
• Design, build, and maintain AI-powered services and APIs, leveraging LLMs (OpenAI, Anthropic, Qwen, OSS models) and custom ML models
• Develop an enterprise-grade agentic framework that enables orchestration, retrieval, and collaboration between multiple AI agents
• Implement and optimize knowledge retrieval systems and agentic search capabilities using vector databases such as Qdrant and ElasticSearch
• Write well-structured, efficient, and testable Python code for production services, experimentation, and internal developer tools
• Build and maintain shared Python libraries and SDKs used across multiple applications and microservices
• Collaborate with cross-functional teams on architecture, internal protocols, and API standards to ensure consistency and reliability across the platform
• Develop and enhance monitoring, validation, and observability for production-grade AI solutions
• Drive the full software development lifecycle - from design and implementation to deployment, monitoring, and continuous improvement
• Identify and resolve performance bottlenecks, reliability issues, and scaling challenges in complex, data-intensive environments
• Participate in code reviews and technical discussions, mentoring other engineers and contributing to a culture of excellence
• Example Projects
• Building an evaluation and observability framework for AI model performance and reliability
• Developing an agentic orchestration platform that enables collaboration among multiple AI agents and tools
• Implementing semantic retrieval and agentic search capabilities over large enterprise knowledge bases
• Designing AI services that process and reason over high-volume real-world data at scale

Требования

• Qualifications / Experience / Technical Skills
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• 7+ years of experience as a Software Engineer, with strong proficiency in Python
• Proven track record of building and maintaining production-grade systems using Python
• Strong understanding of distributed systems, API design, and data-driven architectures
• Experience with relational and non-relational databases (PostgreSQL, Elastic, Qdrant, or similar)
• Familiarity with AI/ML system design, including LLM integration and evaluation pipelines
• Knowledge of DevOps and observability practices (CI/CD, monitoring, metrics, and model validation)
• Python • FastAPI • LLM APIs (OpenAI, Anthropic, Qwen, OSS) • LiteLLM • Qdrant • PostgreSQL • ElasticSearch • Langfuse • Kubernetes • GitHub Actions • ArgoCD
• Excellent communication skills, with the ability to convey complex technical ideas clearly to both technical and non-technical audiences

Будет плюсом

• Experience working with multiple LLM providers (OpenAI, Anthropic, Qwen, open-source models)
• Background in developer platforms or AI infrastructure services
• Familiarity with vector databases, semantic retrieval, and knowledge graph architectures
• Exposure to Langfuse, LiteLLM, LangChain, or similar frameworks
• Experience developing enterprise-scale SaaS or distributed backend systems
• Contributions to open-source projects in Python, AI, or infrastructure engineering
• Soft Skills / Personal Characteristics
• Collaborative and proactive approach, comfortable working across teams in a dynamic environment
• Strong analytical and problem-solving abilities, with a focus on continuous improvement and innovation
• Curiosity and a genuine interest in emerging AI technologies and modern backend architectures
• (REQ ID: 2460)

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