ATG

ATG

Member of Technical Staff (Backend)

New York City · Staff+

Sponsorship not specifiedDetected 371 days ago
PythonGoRustC++Distributed SystemsBackend DevelopmentCode ReviewSQLNoSQLAWSGCPAzureCloud PlatformsDockerKubernetesMachine LearningData EngineeringAgentic AILangGraphA/B TestingResearchMentoring

About the role

  • Your work will enable rapid experimentation, robust data flows, and scalable compute.
  • This is a hands-on role for someone who thrives in small, high-agency teams.

Responsibilities

  • Design and implement scalable backend services, data pipelines, and APIs
  • Build infrastructure for high-throughput, low-latency AI/ML workflows
  • Set up and manage databases (SQL/NoSQL), including schema design, replication, indexing, and performance optimization
  • Optimize for performance, reliability, and security at every layer
  • Implement observability best practices (logging, tracing, monitoring, performance tuning)
  • Work closely with research and infra teams to support experimental velocity
  • 3+ years building distributed systems or high-availability backends (preferably in fast-moving or high-stakes environments)

Requirements

  • Strong proficiency in Python and at least one systems language (e.g., Go, Rust, C++)
  • Experience with cloud platforms, containerization, and orchestration (AWS/GCP/Azure, Docker, Kubernetes)
  • Experience supporting or integrating agentic AI workflows into backend systems (e.g., LangChain, LangGraph, Semantic Kernel, Haystack, or custom frameworks)
  • Familiarity with persistence/checkpointing, streaming pipelines, and vector/knowledge store integrations

Skills

  • Early GPU cloud (9 figure exit).

Company info

  • ATG (Autonomous Technologies Group) is an AI lab deploying frontier reasoning systems within financial markets.
  • Founders: Early GPU cloud (9 figure exit).
  • Investors: Garry Tan / YC + Founder of one of the most successful quant funds, BoxGroup (Plaid, Ramp, Stripe), top-tier angels.

This listing is sourced directly from ATG's careers page and normalized into a canonical job model.