ai engineer for enterprise AI

Workato delivers enterprise infrastructure for the agentic era, helping enterprises unify data, applications, processes, and AI through a governed cloud-native platform. Its architecture connects applications, data sources, and processes to enable real-time orchestration, automation, and enterprise-wide AI operations.

• Design, build, and maintain AI-powered services and APIs using LLMs and custom ML models;
• Develop an enterprise-grade agentic framework for 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 structured, efficient, and testable Python code for production services, experimentation, and internal developer tools;
• Build and maintain shared Python libraries and SDKs used across applications and microservices;
• Collaborate with cross-functional teams on architecture, internal protocols, and API standards;
• 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;
• Mentor other engineers and contribute to a culture of excellence;
• Build an evaluation and observability framework for AI model performance and reliability;
• Develop an agentic orchestration platform for collaboration among multiple AI agents and tools;
• Implement semantic retrieval and agentic search over large enterprise knowledge bases;
• Design AI services that process and reason over high-volume real-world data at scale.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience;
• 5+ Years of experience as a Software Engineer;
• Strong proficiency in Python;
• Proven experience 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, including PostgreSQL, Elastic, Qdrant, or similar;
• Familiarity with AI/ML system design, including LLM integration and evaluation pipelines;
• Knowledge of DevOps and observability practices, including CI/CD, monitoring, metrics, and model validation;
• Excellent communication skills for conveying complex technical ideas to technical and non-technical audiences;
• Collaborative and proactive approach, with the ability to work across teams;
• Strong analytical and problem-solving abilities;
• Curiosity and genuine interest in emerging AI technologies and modern backend architectures;
• Nice to have: experience with multiple LLM providers, developer platforms or AI infrastructure services, vector databases, semantic retrieval, knowledge graph architectures, Langfuse, LiteLLM, LangChain or similar frameworks, enterprise-scale SaaS or distributed backend systems, open-source contributions in Python, AI, or infrastructure engineering.

• No conditions specified