Were growing and looking for someone to own our AI infrastructure-the CI/CD pipelines, cloud environments, and AI automations that keep us shipping fast and reliably.
This is a hands-on software engineering role: youll build internal infrastructure and be involved in product development (real features, not just tooling).
Responsibilities
Own and improve our CI/CD and build/test/release workflows
Own our AWS cloud infrastructure with a strong focus on reliability, security, and cost awareness
Build and maintain internal AI automations that boost developer productivity and reduce manual work
Contribute to product development as part of the core engineering team.
This is a hands-on software engineering role: youll build internal infrastructure and be involved in product development (real features, not just tooling).
Responsibilities
Own and improve our CI/CD and build/test/release workflows
Own our AWS cloud infrastructure with a strong focus on reliability, security, and cost awareness
Build and maintain internal AI automations that boost developer productivity and reduce manual work
Contribute to product development as part of the core engineering team.
Requirements:
Strong engineering fundamentals with an infrastructure + software mindset
Real experience running and improving Jenkins-based pipelines, working in Linux environments, and using Docker to make builds and environments reproducible.
Experience building and maintained systems on AWS and understand cloud infrastructure beyond just deploying an app.
Practical experience on writing and maintaining production code.
Most importantly, hands-on experience building AI automation-for example LLM-based workflows/agents, internal tooling, automation services, evaluation loops, or similar systems that turn AI capabilities into reliable day-to-day engineering leverage.
Nice to have
If you also have experience with web development (front end + back end), thats a plus.
Tcl, C++,
Experience operating in an air-gapped environment (e.g., Vault / sealed-network constraints) is valuable.
Familiarity with GitHub Actions is also a nice bonus.
Strong engineering fundamentals with an infrastructure + software mindset
Real experience running and improving Jenkins-based pipelines, working in Linux environments, and using Docker to make builds and environments reproducible.
Experience building and maintained systems on AWS and understand cloud infrastructure beyond just deploying an app.
Practical experience on writing and maintaining production code.
Most importantly, hands-on experience building AI automation-for example LLM-based workflows/agents, internal tooling, automation services, evaluation loops, or similar systems that turn AI capabilities into reliable day-to-day engineering leverage.
Nice to have
If you also have experience with web development (front end + back end), thats a plus.
Tcl, C++,
Experience operating in an air-gapped environment (e.g., Vault / sealed-network constraints) is valuable.
Familiarity with GitHub Actions is also a nice bonus.
This position is open to all candidates.
