Senior Infrastructure Engineer - AI

Open Select

$150K — $200K *
Telecommunications & Hardware
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3-6 years of experience in building and scaling distributed systems
  • Deep knowledge of cloud infrastructure, particularly AWS
  • Familiarity with high-throughput environments in social or fintech sectors
  • Proven skills in managing real-time processing and low-latency workloads
  • Bachelor's degree in Computer Science or related field from a accredited institution
  • Proficient in Kubernetes, Go, and Datadog; familiarity with GPUs and machine learning infrastructure

Responsibilities

  • Architect and build distributed systems for real-time voice processing using Kubernetes and AWS
  • Design and optimize the ML infrastructure for training and inference across multiple regions
  • Integrate complex telephony systems such as SIP, VOIP, and WebRTC
  • Implement robust monitoring, alerting, and incident response using Datadog
  • Anticipate scaling challenges related to exponentially growing call volumes
  • Enforce security and compliance best practices for enterprise clients

Benefits

  • Equity in a high-growth startup environment
  • Opportunity to influence technology and product direction
  • Work directly with leading VCs and industry founders
  • On-site collaboration in San Francisco, fostering team engagement
  • Access to cutting-edge AI and cloud technologies
Full Job Description
Senior Infrastructure Engineer

Location: On-site, San Francisco, CA (3 days/week in office)
Salary: $150k - $200k + equity
Industry: AI, Cloud Infrastructure
What You'll Drive

Join a fast-growing AI startup backed by $65M from top VCs (Scale Venture Partners, Y Combinator, Emergence, and founders of Twilio, Affirm, ElevenLabs). As a Senior Infrastructure Engineer, you'll architect and scale distributed systems that power millions of real-time, AI-driven phone conversations for major brands and enterprises. Your work will directly impact platform reliability, ML inference performance, and the future of enterprise telephony.

You'll tackle challenges at the intersection of cloud infrastructure, telephony, and machine learning - building systems that handle high-throughput, low-latency workloads and integrating with enterprise-grade voice and video systems. This is a high-impact role with direct influence on product, technology, and company trajectory.
What You'll Focus On
  • Architect and build distributed systems using Kubernetes and AWS for real-time voice processing
  • Design and optimize ML infrastructure for training and inference across multiple regions
  • Integrate with complex telephony systems (SIP, VOIP, WebRTC) and enterprise phone networks
  • Ensure reliability through robust monitoring, alerting, and incident response (Datadog)
  • Anticipate and solve scaling challenges as call volume grows exponentially
  • Implement security and compliance best practices for regulated enterprise customers
Who You Are
  • 3-6 years building and scaling distributed systems, with deep knowledge of cloud infra
  • Experience at high-throughput social/fintech companies or fast-growing startups (Seed-Series C)
  • Proven track record with high-volume, low-latency workloads, streaming, or real-time processing
  • CS degree from a university in the US, Canada, or Europe
  • Skilled in Kubernetes, AWS, Go, Datadog; experience with GPUs, ML infra, and real-time audio/video
  • Background in telephony systems (SIP, VOIP, WebRTC) and/or security and compliance
Tech Stack

Kubernetes, AWS, Go, Datadog, GPUs, SIP, VOIP, WebRTC

Open to US Citizens, Green Card holders, and TN Visa holders only.

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