Menlo Park /
Who We Are:
January AI is a precision health company based in Menlo Park, CA. Founded in 2017 by veteran Silicon Valley business executive, Noosheen Hashemi, and renowned genomicist Mike Snyder, a pioneer in bringing Big Data into personalized medicine, January AI takes a multi-omic approach to (i) understanding the physiology and psychology of the 120 million people on the diabetes spectrum and (ii) developing smart products to help them optimize their blood sugar. By harnessing science, medicine, and machine learning, our technology discovers how diabetes affects people differently and provides specific recommendations to move them to a healthier state.
While multiple technology solutions have appeared in the last decade to address diabetes, innovation has been marginal, making the sector ripe for disruption. We’re leveraging dense data from wearables, smartphones, and digital health; and developed an ontology of 16M food items alongside algorithms like anti-cheat food detection, food recommendations for glycemic load, and 33-hour glucose curve predictions. We also employ social and gamification strategies to keep users engaged with their health and motivated to level up. Together, these tools power our lifestyle intervention programs for improved glucose regulation and metabolic health.
At January AI, we believe that every day is January 1st, that every day is a fresh start. We believe that health isn’t a place you reach, but the simple process of doing just a little better than yesterday. We believe that self-improvement is a team sport. That’s why January AI is creating a community of everyday people building their healthy habits, together. January AI is backed, among others, by Marc Benioff, Jerry Yang and Steve Chen, founders of Salesforce, Yahoo! and YouTube. If you’re ready to join our team and help grow this community, please submit your application following the link provided.
January AI is growing the DevOPS Engineering team to help deploy, manage, troubleshoot, and enhance our complex cloud-based tech-stack for our customers.
-Is Continuous Improvement in your work DNA?
-Do you enjoy working with a highly motivated and talented team to deliver mission-critical health-tech solutions that will change the way people know about their health?
-Do you have experience using AWS with Athena, EMR, Kinesis, Redshift, Glue, SQS
If so, we'd love to talk to you. We are looking for a highly technical, hands-on Engineer with experience using several open source projects commonly found in large-scale deployments.
Roles and Responsibilities:
- You will be automating deployment, monitoring and site reliability for applications in our cloud platform
- You will be managing our existing Jenkins CI/CD pipeline for our mobile application and backend services
- You will be building and managing our machine learning service CI/CD pipelines
- You will be managing our Kubernetes Lifecycle: deployments, upgrades, monitoring, and uptime of all K8S clusters. You will help to advance the deployment process of software into Kubernetes with Terraform Cloud. Additionally, you will work towards perfecting the metrics and alerting on Dynatrace and PagerDuty..
- Your focus will be on minimizing deployment friction and maximizing system uptime. Team members all participate in an on-call rotation.
- You will build innovative automated solutions and tools to help debug and resolve problems in production and prevent them from recurring. Further, you will proactively seek out system weaknesses and find ways to fix them before they cause production issues using monitoring data, watching trends, and using Chaos Engineering.
- You will be keeping our services up and running and quickly recovering when they fail
- You will be working closely with internal stakeholders and teams to ensure that we ship software that meets security, SLA, and performance requirements
- You will be writing and updating user/dev documentation, including runbooks/playbooks
- You will be automating work, including infrastructure tasks, testing, failover solutions, failure mitigation, etc.
- You will be debugging complex problems across the full-stack
- You will be developing CI/CD processes and protections to improve cadence
- You will be using Chaos Engineering to test what you build under real-world conditions
- B.S. in computer science or equivalent
- Extensive cloud experience with AWS; Familiar with AWS technology including Lambda, RDS, SQS, Kinesis, S3, and SageMaker; Experience with Kubernetes including AWS EKS is a plus
- Experience with configuration automation tools Chef, Puppet, Ansible, etc.
- Extensive experience with modern CI/CD tools such Jenkins, CircleCI, etc.
- Extensive experience tracing and logging tools such as DynaTrace, DataDog, ELK, Splunk
- 5+ years designing, building, and operating large-scale distributed systems in production systems at scale
- Solid experience with ML service training, deployment and testing pipeline; Familiarity with Python, JupyterHub and other ML development frameworks
- Strong experiences in production deployment and troubleshooting
- Excellent communication skills, both verbal and written
- A solid understanding of networking and core Internet protocols (e.g. TCP/IP, DNS, SMTP, HTTP, and distributed networks)
- Advanced experience on Terraform
- Understands networking and messaging, especially between services, RPC, gRPC/Proto
- Has hands-on experience using source control (Git, GitHub) and feature branching strategies
- Has experience with a variety of open-source databases (Postgres, Redis, Cassandra, etc.)
- Have a track record of embedding security into the fabric of an organization and infrastructure.
- Understands the idea behind Chaos Engineering
- Experience with Service Mesh (Linkerd/Istio) / API Gateways (Kong/Tyk/AWS) / Message Queuing (Kafka, AWS SQS)
We'd love to hear from you!
January is an equal opportunity employer.
We are a diverse team and are committed to creating an inclusive environment for all employees.
This position is located in Menlo Park, CA. Local or West coast-based candidates preferred.
We do not accept third-party solicitation for employment.