Remote Principal Software Engineer, AI Platform

Alldus

California

On-site

USD 180,000 - 240,000

Part time

14 days+

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Job summary

Alldus International Consulting Ltd in the United States is seeking a Principal Software Engineer to join remotely on a 12-month contract. You will work with the technical co-founder to strengthen architecture and prepare for production release.

This role requires deep backend experience, strong expertise in distributed systems, and hands-on work with Rust or Java and AWS.

Qualifications

  • Experience leading Principal or Senior Staff level engineering teams.
  • Strong backend and distributed systems expertise.
  • Hands-on with proxies, gateways, networking or high-performance data processing.
  • Familiar with AWS production infrastructure and observability.

Responsibilities

  • Evaluate the existing codebase, system architecture and key technical decisions.
  • Partner with the technical co-founder to prepare the platform for production release.
  • Design, build and maintain backend services using Rust and Java.
  • Develop high-performance proxy, gateway and networking capabilities for AI traffic.
  • Enhance the platform's performance, scalability and maintainability.
  • Build observability, monitoring, logging and cost-management capabilities.
  • Identify and address architectural risks ahead of deployments with design partners.
  • Review, test and refactor AI-assisted code produced using Claude and Codex.
  • Introduce pragmatic engineering standards across testing, documentation and code quality.
  • Shape the long-term technical architecture as the company progresses from pre-commercial development to customer deployments.

Skills

Software architecture
Backend engineering
Distributed systems
Rust
Java
AWS
Code quality
Startup experience

Tools

Rust
Java
AWS

Job description

Our client, an early-stage, venture-backed AI Startup, is hiring a Principal Software Engineer to join the team remotely on an initial 12-month contract. The successful candidate will work closely with the technical co-founder to strengthen the platform's architecture, expand engineering capacity and prepare the product for production.


Responsibilities

  • Evaluate the existing codebase, system architecture and key technical decisions.

  • Partner closely with the technical co-founder to prepare the platform for its initial production release.

  • Design, build and maintain reliable backend services using Rust and Java.

  • Develop high-performance proxy, gateway and networking capabilities for managing AI traffic.

  • Enhance the platform's performance, consistency, scalability and maintainability.

  • Build robust observability, monitoring, logging and cost-management capabilities.

  • Identify and address architectural risks ahead of deployments with design partners.

  • Review, test and refactor AI-assisted code produced using tools such as Claude and Codex.

  • Introduce pragmatic engineering standards across testing, documentation and code quality.

  • Shape the long-term technical architecture as the company progresses from pre-commercial development to customer deployments.



Skillset

  • Significant software engineering experience at Principal, Staff or Senior Staff level.

  • Deep expertise in backend engineering and distributed systems architecture.

  • Hands-on experience building proxies, gateways, networking infrastructure or high-performance data-processing systems.

  • Strong proficiency in at least one systems or backend programming language, ideally Rust or Java.

  • Experience designing, deploying and operating production infrastructure on AWS.

  • A strong understanding of system reliability, scalability, latency and performance optimization.

  • The ability to assess an early-stage codebase and implement pragmatic architectural improvements.

  • Experience working within startups, innovation teams or similarly fast-moving and lightly structured environments.

  • The confidence to work independently while collaborating closely with a technical co-founder.

  • Familiarity with AI infrastructure, model gateways, observability or FinOps is a plus.

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