> Markdown version of [/jobs/ext/1450598-ml-engineer-ii](https://www.wearedevelopers.com/jobs/ext/1450598-ml-engineer-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML Engineer II - **Company:** TekWissen LLC - **Location:** Bellevue, WA, United States - **Experience:** Expert - **Salary:** $66,560.0 - $74,880.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Build Automation, Automation of Tests, Cloud Computing, Continuous Integration, Extract Transform Load (ETL), Data Warehousing, Distributed Systems, Software Architecture, Release Management, Reliability Engineering, Power BI, Software Deployment, Software Systems, SQL Databases, Systems Integration, Tableau (Software), Retrieval-Augmented Generation, Large Language Models, Snowflake, Multi-Agent Systems, Kubernetes Helm Charts, Generative AI, Build Management, Gitlab-ci, Kubernetes, Information Technology, Tools for Reporting, Software Coding, Streamlit Framework, Docker - **Published:** July 26, 2026 - **Apply:** https://www.careerjet.com/jobad/usecd428fcf5f3d65bb0708b98bbf1fcb5 ## About the Role * Bachelor'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) * 4 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. Knowledge, Skills and Abilities: * Communication (Required) * Customer Service (Required) * Analytics (Required) * Technical Writing (Required) ## Description * 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 you own, and your growing technical influence within the team. * The work impacts the organization by enabling advanced software capabilities that improve operational efficiency and customer experience., * Contribute 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 our core systems, and build clean abstractions that let non-technical users 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. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Engineering Mindset in the Age of AI - Gunnar Grosch, AWS](https://www.wearedevelopers.com/videos/1735-engineering-mindset-in-the-age-of-ai-gunnar-grosch-aws) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [The Intent Engineer: Closing the Gap Between Business & Engineering - Manuel Klein](https://www.wearedevelopers.com/videos/1855-the-intent-engineer-closing-the-gap-between-business-engineering-manuel-klein) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)