AI Engineer

CodeNinja is a global AI and engineering services company dedicated to helping enterprises build, scale, and operate intelligent systems. With over 350 engineers across four continents and more than 400 successful deployments, the company empowers over 250 clients worldwide to innovate and automate through AI-driven solutions. Recognized as one of Pakistan’s fastest-growing AI firms and a multi-award recipient on Clutch, CodeNinja focuses on delivering practical AI applications via Global Capability Centers, Work AI, Physical AI, and AI Labs.

We are seeking a hands-on AI Engineer to design, develop, and operate AI-powered software systems that provide immediate, real-world value. This role bridges software engineering, product development, and applied AI, with a focus on practical implementation rather than theoretical research. The successful candidate will build and integrate agentic systems, model-driven workflows, and AI-enabled capabilities directly into production applications, internal workflows, and customer-facing products. As part of CodeNinja’s AI-first approach, you will work autonomously, treating models, agents, and context as core runtime components to enhance system leverage, quality, and speed.

Key Responsibilities

- Design, build, and operate production-grade software systems with AI as a core capability.
- Develop and integrate agentic systems that autonomously select tools, manage context, and execute multi-step tasks toward defined goals.
- Implement Model Context Protocol (MCP) or equivalent mechanisms to manage context, tools, memory, and system boundaries in production environments.
- Translate product requirements into scalable, reliable, secure, and observable AI-enabled implementations.
- Apply AI through prompting, orchestration, model composition, evaluation, and deployment, focusing on runtime behavior rather than model training.
- Treat model inputs, outputs, and behavior as versioned, testable components.
- Utilize AI in daily engineering tasks, including AI-assisted code generation, autonomous engineering agents, AI-driven test generation, debugging, refactoring, and documentation.
- Collaborate closely with Product teams, Scrum Masters, and engineers to deliver AI-powered features end-to-end, sometimes acting as a single-person team in a full-stack AI-powered environment.
- Integrate AI systems with real-world services, APIs, and data sources in production applications.
- Ensure quality, security, performance, and compliance of AI-enabled systems, including safeguards, monitoring, and evaluation for AI behavior such as hallucinations and regressions.
- Own solutions from design through deployment and ongoing operation.
- Stay current on AI tools, platforms, models, and agentic patterns; experiment responsibly and contribute to a culture of technical excellence and continuous learning.

Required Qualifications

- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- Strong software engineering fundamentals with experience building and operating production systems.
- Hands-on experience with real agentic AI systems, including autonomy in tool selection and multi-step task execution.
- Experience using Model Context Protocol (MCP) or similar approaches for managing tools, context, and memory in production AI systems.
- Solid understanding of AI models, including knowledge of model versions, parameter sizes, context window limits, system vs. user prompts, and trade-offs such as latency, cost, and reasoning quality.
- Experience with both open-source AI models and commercial or hosted models.
- Proven ability to integrate AI systems with real-world services, APIs, and data sources.
- Capability to evaluate AI systems beyond accuracy, considering reliability, hallucination risk, traceability, and safety.
- Familiarity with scaling concerns like latency, cost optimization, caching, parallelization, and trade-offs between retrieval-augmented generation (RAG) and fine-tuning.
- Demonstrated success in taking AI systems from prototype through pilot to production, with awareness of common failure modes and mitigation strategies.
- Comfortable working autonomously in small, empowered teams.

Preferred Qualifications and Benefits

- Experience integrating frontier and open-source models into SaaS or enterprise applications.
- Familiarity with cloud-native architectures and modern development stacks.
- Background in regulated, enterprise, or mission-critical environments.
- Experience in product-oriented engineering organizations.

Benefits

- Provident Fund (PF)
- Medical Insurance covering spouse and parents up to age 80 (Pakistan)
- Life Insurance
- Performance-Based Increment
- 32 Annual Paid Leaves
- Easy Loan Facility
- Company-Sponsored Trips
- Gym Passport Membership with access to over 250 gyms

CodeNinja is an Equal Opportunity Employer committed to fostering a diverse and inclusive workplace, welcoming candidates regardless of nationality, gender, or background.