Software Engineer, Agent Infrastructure at Netic (San Francisco, CA)
Netic· San Francisco, CA·
Role details
Job description
Netic is the AI revenue engine for essential services who are the backbone of the American economy. With $43M in funding from Founders Fund, Greylock, Hanabi, and Dylan Field who led our Series B, we helped our customers book hundreds of thousands of jobs across services industries in North America. There are now companies operating entirely AI-first on Netic.
You’ll join our team with relentless builders from Scale, Databricks, HRT, Meta, MIT, Stanford, and Harvard in bringing frontier AI to the physical economy, where the problems are hard, the data is complex, and the impact is immediate and tangible.
As an Agent Infrastructure Engineer, you’ll architect and scale the backbone supporting our autonomous AI agents—tackling real-world challenges with immediate, tangible impact. You’ll collaborate with a driven team of builders to shape infrastructure and processes from the ground up, leveraging cutting-edge cloud and orchestration technologies. If you thrive in fast-paced, ambiguous environments and are excited to set new standards in the agentic space, this is your opportunity to build and leave your mark.
WHAT YOU'LL DO
- Build cloud infrastructure: Design and operate the backbone that hosts our AI agents and supports our platform.
- Automate operations: Create infrastructure as code and automated deployment pipelines for reliable releases.
- Enable scale: Implement systems that handle usage spikes gracefully through autoscaling and multi-region support.
- Create observability: Build monitoring, logging, and dashboards that provide real-time visibility into system health.
- Maintain security: Implement security best practices including IAM, network segmentation, and audit trails.
WHAT YOU'LL BRING
- Infrastructure experience: 4+ years running distributed systems at scale with a major cloud platforms (we use GCP but AWS and Azure is great, too).
- Automation and engineering efficiency skills: Proven record of owning infrastructure-as-code and CI/CD pipelines (Terraform, Git Actions, etc).
- Performance expertise: Experience optimizing systems and databases to meet latency and cost targets under multi-modal workloads. For example, experience with pgBouncer, Kubernetes-based autoscaling, and similar tools.
- Observability knowledge: Fluent with modern monitoring and tracing tooling (we use Datadog) and built-in tools in Vercel or GCP.
- Security awareness: Understanding of enterprise security requirements and compliance needs like authentication and service proxies.
- Product mindset: Treat infrastructure as a product and prioritize ambiguous requirements to see around the corner for 1-2 years ahead of our current systems—measure impact and iterate continuously.
- Exposure to AI infrastructure and LLMs. Experience with hosting agents or with LLMs or an interest in experimenting with LLMs - even in your own free time!
What brings us together is our commitment to:
- Live to build
- Run through walls and win
- Obsess over customers in each line of code
- Lose sleep over the "almost perfect"
- Show internal locus of control
- Prioritize finesse: refinement of first principles thinking, execution, and craftsmanship
We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.
Why work at Netic
- Culture & philosophy: Netic describes itself as a team of “relentless builders, ex-founders, and immigrants from top CS schools and tech companies who thrive on solving hard problems.” Cultural values include “live to build,” “run through walls and win,” “obsess over customers in each line of code,” and “prioritize finesse.”
- Work location: HQ in San Francisco (3661 Buchanan St, Fl 4). Most roles appear to be on-site in SF; no explicit remote/hybrid policy stated in available data.
- Engineering culture: Strong bias toward building production-grade, end-to-end AI. Roles like Applied AI Research Engineer, Machine Learning Engineer, and Forward Deployed Agent Engineer indicate a tight feedback loop between development and real-world deployment.
- Notable perks: Opportunity to work on frontier AI technologies (speech, text, multimodal) that directly impact the “backbone of the economy.” The company is at an early stage (32 employees) with significant recent funding, offering high autonomy and ownership.