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Principal Software Engineer

Alldus

California · Posted August 26, 2026

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Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).

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Skills this job asks for

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  • AWS
  • Java

About the job

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.