About TechSee

TechSee is pioneering the future of customer service through Visual and Spatial AI. While most AI understands language, TechSee enables AI to understand the physical world. By combining computer vision, spatial intelligence, conversational AI, and augmented reality, TechSee empowers enterprises to diagnose issues, guide customers, and automate complex service interactions with unprecedented accuracy.

Trusted by leading global brands including Google, Verizon, ADT, and DIRECTV, TechSee helps millions of customers resolve issues faster while reducing operational costs and transforming the customer service experience.

Backed by Salesforce Ventures and Scale Venture Partners, TechSee is building the intelligence layer for the next generation of autonomous physical world customer service.

The Opportunity

We are looking for an DevOps Engineer to join our team and power the infrastructure supporting our enterprise AI platform.

In this role, you will design, automate, and scale mission-critical infrastructure, CI/CD pipelines, and dedicated enterprise environments across a multi-region AWS footprint. Working closely with R&D and Solutions teams, you will tackle enterprise-scale requirements (high availability, tenant isolation, and strict compliance) while leveraging cutting-edge AI tools and agents to accelerate delivery and operational excellence.

Key Responsibilities

• Build, standardize, and scale multi-account, multi-region AWS environments using Terraform.

• Architect and support dedicated enterprise tenant environments, addressing high availability and security hardening.

• Design robust CI/CD pipelines using GitHub Actions or Jenkins, and build custom Python CLIs, Lambda functions, and automation tools to improve developer productivity.

• Integrate AI coding assistants, agents, and custom workflows into internal DevOps processes, incident triage, and root-cause analysis.

• Implement comprehensive observability across metrics, logs, and traces to meet enterprise SLAs, participate in on-call incident response, and lead post-mortems.

• Participate in the infrastructure on-call rotation, responding to production incidents and restoring service availability.
  

Qualifications

• 3–5 years of hands-on experience in DevOps, Platform Engineering, or SRE roles.

• Strong AWS and Terraform experience, including modular infrastructure as code, state management, and multi-account AWS architectures.

• Hands-on experience with Docker and ECS and/or Kubernetes.

• Experience building reliable CI/CD pipelines using GitHub Actions, Jenkins, or similar platforms.

• Python skills for developing tools, CLIs, and AWS automation with boto3, alongside solid Linux, and networking fundamentals.

• Familiarity with VPC architecture, private networking such as Direct Connect and PrivateLink, least-privilege IAM roles, and enterprise security standards.

• Daily use of AI coding assistants, with demonstrated experience securely building or integrating custom AI workflows, agents, or operational automation.

Why Work With Us?

• Real-World AI Impact: Power the infrastructure behind Visual and Spatial AI used by industry-leading global enterprises.

• AI-Native Engineering: Work in an environment that actively embraces AI agents and automation to eliminate toil.

• End-to-End Ownership: Take full ownership of complex cloud architecture, developer tooling, and enterprise infrastructure projects.

• Collaborative Culture: Join a supportive, high-velocity engineering team that values knowledge sharing and pragmatic innovation.

• Hybrid Work & Flexibility: Enjoy a flexible hybrid work model combining office and remote work.