Design and develop production-grade systems that power intelligent automation, agentic workflows, and large-scale retrieval services.
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.

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, 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).

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.

Workato is hiring a Senior Software Engineer (MLAI services)