We have been a remote-first organization since our inception and are passionate about work-life balance, building impactful teams, and committed to creating environments that encourage collaboration, different points of view, and creative solutioning.
Truss is looking for a skilled, hands-on DevSecOps or platform engineer.
This person will stand up, secure, and operate the AWS environment that powers AI capabilities on a large federal program, and will support the cloud infrastructure underneath that program's applications more broadly. A secondary part of the role is data engineering for that platform: ingesting and preparing the documents and structured data that AI workflows depend on.
You will partner with program engineers who bring deep domain and data knowledge, so this job is the infrastructure and the plumbing, with domain expertise available to you rather than expected of you. You will also be the reference point for AI infrastructure on AWS, so you should be comfortable setting patterns other engineers will follow and supporting more than one application team at a time.
The work is meaningful and the team is dedicated, but the program carries real security, privacy, and data retention obligations, and everyone is expected to perform and contribute at a high level.
In addition, like everyone at Truss, this person should have excellent communication skills, a collaborative approach, and high emotional intelligence.
This role is expected to work 35 hours per week including the core hours of 10:00am - 4:00pm ET
Must be able to travel to Baltimore, MD twice per calendar year.
Hourly rate is $80 - $88 dependent on experience.
Contract lasts through April 2027 with potential extension.
Required Qualifications
- Experience supporting AI or machine learning models on AWS: provisioning, deploying, and operating AI services in production (e.g., Amazon Bedrock, SageMaker), including the data pipelines that feed them
- 3+ years of experience in DevSecOps, Platform Engineering, Site Reliability Engineering (SRE), or Cloud Infrastructure Engineering
- Experience building and operating cloud-native applications on AWS
- Experience with Infrastructure as Code and CI/CD pipeline development
- Experience with containerization (Docker) and orchestration (e.g., ECS, EKS)
- Experience with identity and access management, secrets management, and cloud security best practices
- Strong Python skills and working SQL, with hands-on experience building data pipelines (e.g., S3, Glue, Lambda, Step Functions)
- Experience implementing monitoring, logging, and observability solutions
- Strong troubleshooting and problem-solving skills
We use AI tools in our work as appropriate.
Our interview will not require you to write any code. We will ask you to walk through code and infrastructure with us, and we will want to know whether you're able to operate as an engineer who can distinguish and clearly explain the difference between good work and substandard AI-generated work. Following that reasoning, we ask that you please do not use any AI tools during the interview itself.
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