Senior Software Engineer, AI SaaS Software

New

Based in India, UTC−6 to UTC+2, spanning North American Central Time through Central European Summer TimeFull-TimeSenior

Salary not disclosed

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Job Details

Experience: At least 7 years of professional software engineering experience
Required Skills: AWSPostgreSQLJavascriptRedisReactScala

At least 7 years of professional software engineering experience building and maintaining production systems.
Strong backend engineering expertise in Scala or comparable languages such as Java, Ruby, or C#.
Solid JavaScript and React experience.
Demonstrated experience building, scaling, and evolving SaaS products in production.
Deep familiarity with AI-powered coding tools such as Claude Code, Codex, Cursor, or comparable agentic development solutions.
Practical experience with multi-session coding environments and agent-driven workflows, including context and task management.
Strong judgment in evaluating when to use AI-generated solutions versus manual implementation or further investigation.
Experience designing systems and architectures.
Ability to build or customize AI-assisted workflows, internal engineering tools, reusable prompts, and agent-based systems.
Ability to move between implementation, system design, AI-agent guidance, debugging, and code review.
Excellent written communication and ability to collaborate in an asynchronous, distributed team.
Availability to work within the team's preferred time zones, approximately UTC−6 to UTC+2.

Architect and evolve scalable backend systems using Scala, Play Framework, PostgreSQL, Redis, AWS, and related technologies.
Design, develop, and deploy reliable APIs and AI-assisted services.
Own end-to-end feature development, including implementation, testing, deployment, and production support.
Build and maintain frontend experiences using React and the listed frontend tools.
Develop and maintain agent-driven engineering workflows for coding, debugging, and refactoring.
Use AI coding tools while evaluating generated code for maintainability, reliability, and quality.
Create internal developer tools, reusable prompts, AI skills, and automation systems.
Optimize performance across frontend applications, backend services, APIs, infrastructure, and AI-assisted development pipelines.
Establish practices for AI-native software development and human-AI collaboration.
Help define technical direction and development practices while progressing toward leading a small team of two to three engineers.

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