Senior AI Engineer

Key Responsibilities

• Design, build, and operate scalable backend services, APIs, and AI agents driven by large and small language models (LLMs and SLMs), engineered for production reliability from day one.

• Architect and administer databases that power AI functionality at scale, designing efficient, performant data models that hold up under real-world load.

• Integrate external APIs and services to embed AI capabilities into existing business systems and workflows without compromising stability or performance.

• Establish comprehensive automated testing across unit, functional, integration, and performance layers to guarantee production readiness.

• Build and maintain robust CI/CD pipelines using DevOps and MLOps practices to deploy, monitor, and evaluate applications and services in live production environments.

• Diagnose and resolve bugs and field issues quickly, and produce clear documentation as needed to support customers and business partners.

• Partner with product managers and AI engineers to deliver complete, production-quality solutions.

Minimum Qualifications and Experience

• Advanced degree (BS/MS) in Computer Science or equivalent technical discipline. We prioritise tangible impact over tenure; you should demonstrate clear ownership of production-grade AI/ML or backend services through professional work, open-source contributions, or sophisticated personal engineering projects.

Required Expertise

• Strong grounding in computer science fundamentals such as data structures, algorithms, programming, design patterns, virtualization, and so on, paired with sharp problem-solving abilities.

• Commitment to high code-quality standards (clean, well-documented, modular, maintainable, reliable, efficient, secure coding) and automated testing that stands up to production demands.

• Practical experience with backend frameworks such as Node.js, Django, Flask, and FastAPI.

• Proven experience building and scaling large-scale microservices and applications on cloud platforms (e.g., AWS, GCP, Azure) using containerization and orchestration tools (e.g., Docker, Kubernetes).

• Familiarity with SQL and NoSQL databases, including the ability to write complex queries and optimize database performance at scale.

• Collaborative team player with strong interpersonal skills and the ability to work effectively alongside remote teammates.

• Proactive, go-getter mindset and the ability to thrive in a fast-paced startup environment.

Preferred Skills

• Experience with or working knowledge of any of the following is a strong plus:

• Building AI/ML applications such as AI agents, chatbots, and automation workflows.

• Vector databases, embeddings, and retrieval-augmented generation (RAG).

• Model Context Protocol (MCP), Agent-to-Agent (A2A), and Agent Communication Protocol (ACP).

• AI/ML tools such as PyTorch, TensorFlow, LangChain, LlamaIndex, and similar.