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 ResponsibilitiesDesign, develop, and optimize AI agents for enterprise workflowsBuild agentic workflows that automate processes and surface insightsIntegrate LLMs and AI services into production environmentsLeverage APIs and AI SDKs to extend agent capabilitiesDevelop backend services and integrations using PythonSupport AI workloads on GCP (BigQuery and cloud-native services)Optimize agent performance, token usage, and costCollaborate with business stakeholders on real-world use casesBuild scalable, maintainable AI solutions and ensure operational excellence Key requirementsStrong Python development experienceExperience building or supporting AI Agents and Agentic WorkflowsExperience with LLMs and Generative AIExposure to AI SDKs (OpenAI, Anthropic, or similar)Experience integrating APIs into AI-driven solutionsGCP experience including BigQueryExperience working with unstructured dataUnderstanding of AI agent optimization, deployment, and operational performanceHands-on experience with agent orchestration frameworks (LangChain, LangGraph, or Google ADK)Collaborative problem solvingStakeholder communicationAnalytical mindsetPythonLLMs and Generative AIOpenAI and Anthropic SDKs