AI Engineer
Bachelor's in CS/Engineering or related field; 4+ years in AI-enabled software; strong software fundamentals; autonomous in small teams; experience with frontier AI models or SaaS/enterprise integration is a plus.
About the Company
CodeNinja is a global AI and engineering services company helping enterprises build, scale, and operate intelligent systems. With 350+ engineers across four continents and 400+ successful deployments, CodeNinja enables organizations to harness artificial intelligence through Global Capability Centers, Work AI, Physical AI, and AI Labs. Recognized among Pakistan’s fastest-growing AI firms and a multi-award recipient on Clutch, CodeNinja empowers over 250 clients worldwide to innovate, automate, and compete in the intelligence economy.
About the role
We are looking for a hands-on AI Engineerresponsible for designing, developing, and operating AI-powered software systemsthat deliver immediate, real-world value. This role sits at the intersection of software engineering, product engineering, and applied artificial intelligence, with a strong focus on practical implementation rather than research or theoretical model development. As part of CodeNinja’s AI-first operating model, you will leverage LLMs, AI agents, and automationto fundamentally improve how software is built, deployed, and operated.
Key Responsibilities
- Design, build, and operate production-grade software systemswith AI embedded as a core capability.
- Apply agentic solutionsand automation frameworksto solve concrete business and product challenges.
- Translate product requirements into scalable, secure, and reliable AI-enabled solutions.
- Focus on applied AI usage including prompting, orchestration, integration, evaluation, and deployment.
- Use AI directly in daily engineering work, including AI-assisted code generation, debugging, refactoring, and test creation.
- Continuously evolve AI usage across the software development lifecycleto improve speed, quality, and leverage.
- Collaborate closely with Product, Scrum, and Engineeringteams to deliver AI-powered features end to end.
- Contribute to shared platforms, services, and internal toolsthat enable AI-native development at scale.
- Ensure AI-enabled systems meet standards for security, performance, and reliability.
- Implement monitoring, safeguards, and evaluation mechanismsfor AI behavior in production.
- Take full ownership of solutions from design through deployment and ongoing operation.
- Stay current with emerging AI tools, platforms, and implementation patterns.