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 organizations worldwide to harness artificial intelligence through its Global Capability Centers, Work AI, Physical AI, and AI Labs. Recognized as one of Pakistan’s fastest-growing AI firms and a multi-award recipient on Clutch, CodeNinja serves over 250 clients, enabling them to innovate, automate, and compete effectively in the intelligence economy.

We are seeking a hands-on AI Engineer to design, develop, and operate AI-powered software systems that deliver tangible, real-world value. This role bridges software engineering, product engineering, and applied AI, focusing 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 CodeNinja advances its AI-first approach, you will work autonomously, treating models, agents, and context as core runtime components to enhance leverage, quality, and speed in the systems you manage.

Key Responsibilities

- Design, build, and operate production-grade software systems embedding 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 similar mechanisms to manage context, tools, memory, and system boundaries in production.
- Translate product requirements into scalable, reliable, secure, and observable AI-enabled implementations.
- Apply AI techniques such as prompting, orchestration, model composition, evaluation, and deployment, focusing on runtime behavior rather than model training.
- Treat model inputs, outputs, and behavior as versioned, testable system components.
- Use AI in daily engineering work, including AI-assisted code generation, autonomous engineering agents, AI-driven testing, debugging, refactoring, documentation, and observability.
- Iterate on prompts, policies, agent flows, and contextual inputs as part of the development workflow.
- Collaborate closely with Product, Scrum Masters, and engineers to deliver AI-powered features end-to-end, sometimes acting as a single-person full-stack team.
- Integrate AI systems with real-world services, APIs, and data sources in production applications.
- Contribute to shared platforms, services, and internal tooling following architectural guidelines.
- Own the quality of deliverables across the full stack, building AI agents to ensure quality and partnering with QA when available.
- Ensure AI-enabled systems meet enterprise standards for security, performance, reliability, and compliance.
- Implement safeguards, monitoring, and evaluation for AI behavior in production, including detection of hallucinations and unintended behavior.
- Maintain evaluation, traceability, and explainability as ongoing engineering priorities.
- Stay current on AI tools, platforms, models, and agentic patterns relevant to real-world software.
- Experiment responsibly with new AI capabilities 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 with Model Context Protocol (MCP) or equivalent approaches for managing tools, context, and memory in production AI systems.
- Solid understanding of AI models, including model versions, parameter sizes, context window limits, system vs. user prompts, and trade-offs related to 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.
- Knowledge of scaling concerns such as latency, cost optimization, caching, parallelization, and trade-offs between retrieval-augmented generation and fine-tuning.
- Demonstrated ability to take 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.
- Experience in regulated, enterprise, or mission-critical environments.
- Background 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 Paid Annual 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 an inclusive environment for all employees, regardless of nationality, gender, or background.