Full-Time

Infrastructure Engineer

Infra Engineer

Updated on 9/10/2026

NeoSigma

NeoSigma

1-10 employees

Autonomous ML engineer automating ML workflows

No salary listed

Bengaluru, Karnataka, India

In Person

Bachelor's

Category
DevOps & Infrastructure (1)
Required Skills
Kubernetes
SOC 2
SAML
Cryptography
Terraform
Observability
DevOps
HIPAA
Google Cloud Platform

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Requirements
  • The candidate must have shipped real infrastructure at a startup and lived with the operational consequences.
  • The candidate must have strong fundamentals across Google Cloud Platform, Kubernetes, and Terraform.
  • The candidate must have experience with enterprise deployment patterns including Bring Your Own Cloud, Virtual Private Cloud isolation, SSO/SAML/SCIM, and compliance.
  • The candidate must apply a security-first approach, including understanding blast radius, attack surface, and audit trails.
  • The candidate must be comfortable writing technical design documents and operational runbooks.
  • The candidate must have a Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Responsibilities
  • Design and ship enterprise-grade deployment architecture across multi-cloud Google Cloud Platform, Bring Your Own Cloud, and Virtual Private Cloud-isolated environments for regulated customers.
  • Own data retention policies end-to-end, including minimal collection, defined time-to-live periods, personally identifiable information handling, and data residency by default.
  • Build private and secure connectivity solutions using Virtual Private Cloud peering, PrivateLink, and Private Service Connect for customer-managed environments.
  • Own critical continuous integration and continuous delivery infrastructure, including pipelines, deployment automation, and rollout and rollback tooling across the full stack.
  • Architect security from the ground up, including identity and access management, secrets management, least-privilege access, encryption, and audit logging by default.
  • Own enterprise deployment relationships, including SSO/SAML/SCIM, network configuration, and compliance documentation for SOC 2, HIPAA, and GDPR.
  • Build and maintain observability across distributed deployments, including structured logging, metrics, alerting, and on-call practices.

NeoSigma builds an AI product lab behind an intelligent automation layer called NEO. NEO acts as an autonomous ML engineer that handles the full machine learning workflow: data science tasks, model training, fine-tuning large language models, building retrieval-augmented generation pipelines, running evaluations, and deploying production-ready AI systems. It works by using multiple agents in parallel inside a GPU sandbox to run hundreds of experiments, measure their performance against targets, and pick the best models. Users can interact with NEO via a chat interface to guide exploration and provide context. NeoSigma can fix training pipelines, add new AI features to existing projects, and check for data leakage in pipelines. The goal is to connect customers, products, and AI systems by delivering automated, end-to-end ML development that speeds up building and deploying AI-powered products.

Company Size

1-10

Company Stage

N/A

Total Funding

N/A

Headquarters

San Francisco, California

Founded

2025

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Simplify Jobs

Simplify's Take

What believers are saying

  • March 2026 auto-harness results showed Tau3 performance rising from 0.56 to 0.78.
  • July 2026 posts show active partnerships with Daytona and Exa around agent infrastructure.
  • Careers and founder posts in 2026 show hiring momentum and backing from Jeff Dean, OpenAI, and DeepMind leaders.

What critics are saying

  • NeoSigma is still in stealth, so revenue, customers, and retention remain unproven.
  • Its value depends on production agent adoption; OpenAI and Google can bundle similar tooling fast.
  • If sandbox-driven agent maintenance commoditizes, NeoSigma becomes a feature, not a company.

What makes NeoSigma unique

  • NeoSigma builds self-improving agent infrastructure, not just another chatbot, per March 2026 blog.
  • Its sandboxed workspaces mirror developer environments, with Docker, repos, networking, and reproducibility.
  • The company markets production feedback loops that mine failures into reusable evals and harness fixes.

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Benefits

Health Insurance

Paid Vacation

Flexible Work Hours

Company Equity