Senior DevOps Engineer

About Karta -

Karta builds production AI agents for enterprises. Our platform powers real-time voice and chat agents that integrate with enterprise systems, make API calls, automate workflows, and operate reliably at production scale.

Behind every conversation is production infrastructure: cloud environments, CI/CD, observability, telephony and media workloads, and the deployment path every engineer ships through.

Our engineering spans AWS, Azure, and GCP, and engineers regularly work across cloud infrastructure, distributed systems, AI infrastructure, and real-time communications.

We're still early enough that a single engineer can fundamentally shape how we build and operate, yet

mature enough that reliability, security, and long-term ownership matter every day

Role Description

• We're looking for a Senior DevOps Engineer who enjoys owning production systems rather than running a ticket queue.

You won't spend your time waiting for perfectly written specifications. Instead, you'll take ambiguous

reliability and delivery problems, design practical solutions, ship them, operate them, and keep improving them after launch.

Over time, you'll become the long-term owner of critical platform systems: how we deploy, observe, and runproduction.

What You'll Do

You'll be trusted to own significant platform initiatives end-to-end across critical infrastructure: cloud

environments, CI/CD, observability and incident response, runtime platforms for real-time voice and media, and the security and access foundations those systems depend on.

That means you'll:

• Own the design, implementation, and evolution of those systems, from cloud architecture and deployment through networking and operational reliability.
• Establish and improve engineering practices around infrastructure as code, change safety, observability, and production readiness.
• Identify bottlenecks in delivery and reliability, and lead improvements in scalability, cost, security, and operability.
• Mentor engineers and help them grow in operational judgment and ownership.
• Work closely with engineering leadership to evaluate trade-offs between reliability, cost, complexity, and delivery speed.
• Stay hands-on: write infrastructure and automation, review designs, debug production incidents, and ship meaningful improvements.
• Raise engineering standards through design reviews, operational reviews, mentoring, and knowledge sharing.

What We're Looking For - Must Have!!

• Typically 6+ years of professional experience building and operating production infrastructure, with demonstrated ownership of complex systems.
• Demonstrated ownership of significant platform work from design through production, Experience with AWS, Azure or GCP.
• Strong proficiency with infrastructure as code at scale (CDK, Terraform, or similar), CI/CD, GitHub Actions or equivalent.
• Strong understanding of Linux, networking, containers, and how distributed services fail in production.
• Experience operating Kubernetes or ECS-style container platforms, and with queues, load balancing, and autoscaling.
• Good judgment around reliability, security, cost, and delivery speed.
• A high bar for automation, observability, and operational excellence.
• Experience mentoring engineers and improving team-wide engineering practices.
• An ownership mindset: someone who takes responsibility for outcomes, including on-call, not just assigned tasks.

Nice to Have

Experience with any of the following is a strong plus:

• Real-time or media infrastructure: WebRTC, telephony, or streaming workloads.
• Experience managing SIP servers.
• Multi-account or multi-region cloud design, VPNs, and private connectivity for enterprise customers.
• Observability stacks, SLOs, and incident management in a product company.
• Security and compliance work such as access control, secrets management, or audit logging.

How We Work

• Small engineering team with high trust and minimal bureaucracy
• Engineers own problems, not just tickets
• Fast iteration balanced with production reliability
• Technical decisions are driven by reasoning and data, not hierarchy
• Strong emphasis on systems that stay operable as the company scales
• Growth follows sustained impact—not tenure or title