GRACEMARK - MACHINE LEARNING ENGINEER

AI Engineer is needed in Bellevue, United States.Client: GracemarkLocation: Bellevue, WAContract: ContractJob DescriptionPosition: ML Engineer IILocation: Bellevue, WADuration: 6 MonthsJob Type: Temporary AssignmentWork Type: HybridThis role is essential for designing, building, and deploying scalable, generative AI-enabled software solutions that meet customer requirements and support high-availability environments. It involves collaborating with engineers to develop software components using modern CI/CD and deployment practices such as blue-green deployments, observability, canary deployments, Kubernetes, feature flags, and automated rollbacks, as well as building and maintaining reporting and dashboards that provide ongoing visibility into GenAI operations. The role requires applying sound engineering judgment to resolve technical issues and contributing to generative AI-enabled software architecture and design, with a focus on releasing and triaging deployed software. Success is measured by the delivery and effectiveness of generative AI-enabled software solutions, the quality and reliability of the components owned, and the growing technical influence within the team. The work impacts the organization by enabling advanced software capabilities that improve operational efficiency and customer experience.Job ResponsibilitiesContribute to the architecture, design, and production deployment of enterprise-scale software releases using generative AI systems, including LLM orchestration, agent/skill creation, retrieval-augmented generation, evaluation, and operational monitoring.Design and implement modular AI agents that connect to core systems, and build clean abstractions for non-technical users to leverage these agents in useful workflows without writing code.Build automation that streamlines release operations, operational reporting, and engineering workflows for generative AI-enabled systems.Build and deploy containerized services and automation—packaging applications as Docker images, authoring Helm charts, and deploying to Kubernetes—and build and maintain the CI/CD pipelines (GitLab CI) that automate build, test, and release.Build and maintain dashboards and reports that provide ongoing visibility into release health, model and system performance, and operational metrics for deployed GenAI solutions.Build observability capabilities through dashboards, monitoring, alerting, tracing, and operational telemetry.Troubleshoot complex production issues across applications, cloud infrastructure, Kubernetes, APIs, distributed systems, and enterprise integrations.Provide technical guidance by mentoring junior engineers and contributing to technology decisions within the team.Apply and help improve GenAI engineering standards, reference architectures, and guardrails that ensure scalability, security, cost efficiency, and responsible AI use.Contribute reusable templates, patterns, and documentation that accelerate the team’s ability to deliver.Develop generative AI-enabled software designs and improvements that enhance existing systems and processes.Produce clear technical documentation and architecture descriptions for internal and external stakeholders.Collaborate closely with Product Management, Platform Engineering, SRE, Security, UX, and engineering teams to deliver scalable, secure, and reliable software solutions.Also responsible for other duties/projects as assigned by business management as needed.RequirementsBachelor’s Degree plus 4 years of related work experience OR Advanced degree with 2 years of related experience (Required)Acceptable areas of study include Computer Science or Engineering (Required)Preferred Qualifications4–7 years of technical engineering experience (Required)Hands-on experience building and shipping GenAI features in production (LLM orchestration, agent frameworks, RAG) that serve real users reliably.Experience applying AI engineering standards, reference architectures, and governance models within a team or product area.Demonstrated ability to build composable AI components and internal tooling that enable non-technical users to build workflows without engineering support.Experience mentoring engineers and collaborating across functions to deliver shared outcomes.Experience with release management and CI/CD deployment best practices.Hands-on experience building services and automation scripts, authoring Dockerfiles and Helm charts, deploying to Kubernetes, and building and maintaining CI/CD pipelines (GitLab CI or similar).Experience with data warehousing, SQL, and ETL processes, ideally including Snowflake.Experience building dashboards and reports with BI and reporting tools such as Power BI, Streamlit, Tableau, or similar.CompensationPay: $55.00 - $60.00 per hourWork LocationHybrid remote in Bellevue, WA 98007Posted an hour ago