About Us:
Co-founded in 2023 by Joe Laws and Grant Verstandig, Trase Systems is AI, Uncomplicated. Trase empowers enterprise leaders to harness the full potential of AI without the associated complexity and risks. We are an end-to-end solution for deploying, managing, and optimizing AI in the enterprise. Our platform specializes in bridging the “last mile” of AI adoption, unlocking AI's full potential while driving efficiency and significant cost savings. Trase is at the forefront of AI Agent innovation, topping the Hugging Face GAIA Leaderboard for Generalized AI Assistants, ahead of industry giants such as Google, Meta, Microsoft, and OpenAI. We are leveraging our cutting-edge technologies to develop mission-critical agentic applications in complex industries such as Healthcare, Oil & Gas, and National Security.
About the Role
Are you passionate about building and maintaining the resilient, scalable infrastructure that powers cutting-edge AI? Do you excel at ensuring the reliability and performance of complex, distributed systems? If you thrive on automating, monitoring, and optimizing the platforms that enable machine learning innovation, we have an exciting opportunity for you as a Site Reliability Engineer at Trase Systems.
As a Site Reliability Engineer, you will be a cornerstone of our engineering team, responsible for the availability, latency, performance, and capacity of Trase's AI platform. You will work closely with our ML engineers, software engineers, and product teams to build and operate the infrastructure that runs our advanced AI agents and machine learning models. If you are a proactive problem-solver with a passion for building highly reliable systems in a fast-paced, innovative environment, we invite you to join our mission.
Responsibilities
- Design, Build, and Maintain Core Infrastructure: Architect and implement scalable, highly available, and secure infrastructure on cloud platforms (GCP, AWS, Azure) to support our AI-driven applications and services.
- Automate Everything: Develop and maintain automation tools and frameworks to eliminate manual effort in deployment, configuration, and management of our production environment.
- Ensure System Reliability and Performance: Establish and monitor Service Level Objectives (SLOs) and Service Level Indicators (SLIs) for our production systems. Proactively identify and resolve performance bottlenecks and availability issues.
- Manage ML Infrastructure and Pipelines: Collaborate with ML engineers to build and maintain robust CI/CD pipelines for machine learning models, ensuring seamless training, deployment, and monitoring.
- Incident Response and Post-Mortems: Lead incident response efforts to minimize downtime and conduct thorough post-incident reviews to identify root causes and implement preventative measures.
- Implement and Enhance Observability: Deploy and manage comprehensive monitoring, logging, and tracing solutions (e.g., Prometheus, Grafana, ELK stack) to provide deep visibility into system health.
- Capacity Planning and Cost Optimization: Forecast infrastructure needs and optimize resource utilization to ensure our platform can scale efficiently and cost-effectively.
- Foster a Culture of Reliability: Champion SRE best practices across the engineering organization and mentor team members on reliability, performance, and scalability.
Requirements
- Proven SRE and DevOps Experience: Demonstrated experience in a Site Reliability Engineering or DevOps role, managing complex, large-scale production environments.
- Cloud Infrastructure Expertise: Hands-on experience with one or more major cloud platforms (GCP, AWS, Azure).
- Proficiency in Infrastructure as Code: Strong skills with IaC tools such as Terraform, Ansible, or CloudFormation.
- Containerization and Orchestration Mastery: Deep knowledge of Docker and Kubernetes, including experience deploying and managing containerized applications in production.
- Strong Programming and Scripting Skills: Proficiency in languages such as Python, with a focus on automation and building reliable software.
- Experience with Monitoring and Observability Tools: Expertise in setting up and using monitoring and logging systems like Prometheus, Grafana, or the ELK stack.
- CI/CD Pipeline Development: A strong background in building and managing CI/CD pipelines for both software applications and machine learning models.
- Excellent Problem-Solving and Communication Skills: The ability to troubleshoot complex issues across the stack and clearly communicate technical concepts to both technical and non-technical stakeholders.
- Educational Background: A Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
- Active Security Clearance required.
Benefits
- 100% employer-paid, comprehensive health care including medical, dental, and vision for you and your family.
- Paid maternity and paternity for 14 weeks at employees' normal pay.
- Unlimited PTO, with management approval.
- Opportunities for professional development and continued learning with educational reimbursements.
- Optional 401K, FSA, and equity incentives available.
- Mental health benefits through TARA Mind.
Some travel is required.
If you want to be on the cutting edge of technology, building AI solutions for the future, and are up for a challenge, let’s talk!
We’re an Equal Opportunity Employer: You’ll receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.
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