Machine Learning Engineer

Overview In this role you will design and operationalize AI agents to automate and optimize enterprise workflows. You will integrate LLMs and AI services into production, building scalable, maintainable AI solutions that improve decision-making across business domains. You will collaborate with stakeholders to translate real-world use cases into deployed AI workflows, focusing on performance, cost efficiency, and reliability in cloud environments. This is a hands-on, production-first engineering role at a company known for innovation and continuous learning. Compensation / Benefitsmedical, dental, vision, life, disability insuranceESPP (employee stock purchase program)401K with company matchHSA (Health Savings Account)EAP with counseling sessionscertification discounts and training resources Responsibilities Design, develop, and optimize AI agents for enterprise workflows Build agentic workflows that automate processes and surface insights Integrate LLMs and AI services into production environments Leverage APIs and AI SDKs to extend agent capabilities Develop backend services and integrations using Python Support AI workloads on GCP (Big Query and cloud-native services)Optimize agent performance, token usage, and cost Collaborate with business stakeholders on real-world use cases Build scalable, maintainable AI solutions and ensure operational excellence Key requirements Strong Python development experience Experience building or supporting AI Agents and Agentic Workflows Experience with LLMs and Generative AIExposure to AI SDKs (OpenAI, Anthropic, or similar)Experience integrating APIs into AI-driven solutionsGCP experience including Big Query Experience working with unstructured data Understanding of AI agent optimization, deployment, and operational performance Hands-on experience with agent orchestration frameworks (Lang Chain, Lang Graph, or Google ADK)Collaborative problem solving Stakeholder communication Analytical mindset PythonLLMs and Generative AIOpenAI and Anthropic SDKs