We are looking for a
Principal Engineer to serve as the technical expert for our AI Platform & Operations. This isn't just a role about maintaining infrastructure; it's about
owning the technical vision for the foundational systems that will power every AI product team across the company.
Remote Role - can be based in either Washington or California State.
RequirementsBy building robust, self-serve internal developer platforms, you'll enable our engineers to deploy, monitor, and scale AI models with unprecedented efficiency and safety. Your work ensures that our "Agentic" future is reliable, cost-effective, and cutting-edge.
What You'll Be Doing- Architect the Future: Define the long-term technical roadmap for our AI platform, covering everything from model serving and feature stores to experiment tracking and CI/CD for ML.
- Set the Gold Standard: Establish engineering benchmarks for deployment, versioning, A/B testing, and automated rollbacks.
- Optimize & Scale: Lead strategies for GPU/compute efficiency and cost optimization while managing the complexities of LLM inference (quantization, batching, and latency) at scale.
- Enhance Observability: Design sophisticated monitoring and alerting systems specifically tailored for AI workloads in production.
- Champion Reliability: Drive platform stability and partner with application teams to ensure our infrastructure meets evolving product needs.
- Technical Leadership: Mentor Senior engineers, lead architecture reviews, and evaluate the next generation of cloud services and ML frameworks.
What You'll BringWe are looking for a heavy-hitter in the ML infrastructure space who thrives on solving complex, distributed systems problems.
- Senior Expertise: 12+ years of engineering experience, with at least 4 years at a Principal or Distinguished level.
- ML Infrastructure Mastery: Expert-level knowledge of model serving (e.g., Triton, vLLM, Ray Serve) and deep experience with Kubernetes and cloud ecosystems (AWS/GCP/Azure).
- The MLOps Toolkit: Proven experience with tools like MLflow, Weights & Biases, or Kubeflow.
- Coding & Systems: High proficiency in Python and a "systems-thinking" approach to Docker, Helm, and containerization.
- AI Specialization: Hands-on experience operating LLM inference at scale and a deep understanding of the trade-offs between throughput and latency.
- Platform Mindset: A track record of building internal platforms that treat other engineers as the primary customer, drastically improving engineering velocity.
BenefitsAt Serko, we aim to create a place where people can come and do their best work. This means you'll be operating in an environment with great tools and support to enable you to perform at the highest level of your abilities, producing high-quality and delivering innovative and efficient results. Our people are fully engaged, continuously improving, and encouraged to make an impact.
Some of the benefits of working at Serko are:
- A competitive base pay
- Medical Benefits
- Discretionary incentive plan based on individual and company performance
- Focus on development: Access to a learning & development platform and opportunity for you to own your career pathways
- Flexible work policy
- The pay range is between $168,000 - $230,000 USD as a base salary offering annually.
