The AI Engineer is a new-generation engineering role combining strong software development, computer-science foundations, product thinking, and practical AI-assisted development. This role is not limited to classic machine learning research. It is closer to the modern full-stack developer: able to understand a product need, design the technical solution, build it, test it, deploy it, and maintain it using advanced AI development tools. The ideal candidate knows how to use tools such as Claude Code, Cursor, GitHub Copilot, Codex, or similar assistants to improve speed and quality, while still maintaining full engineering responsibility for architecture, security, code quality, testing, and production stability.
Key Requirements * Strong software engineering background with the ability to design, build, test, and maintain production-grade applications. * Ability to manage complex development projects end to end, from requirements and technical design through implementation, deployment, and support. * Practical experience with AI-assisted development tools such as Claude Code, Cursor, GitHub Copilot, Codex, or equivalent tools. * Strong understanding of backend systems, APIs, databases, integrations, authentication, logging, testing, and deployment workflows. * Working knowledge of AI/LLM concepts, including prompt engineering, RAG, embeddings, vector databases, model APIs, evaluation, and AI system limitations. * Ability to review and validate AI-generated code rather than blindly accepting it. * Strong ownership mindset and ability to work independently with minimal supervision. * Good communication skills and ability to translate product/business needs into clear technical tasks and deliverables.
Qualifications * Degree in Computer Science, Software Engineering, AI, Data Science, or equivalent practical experience. * 3+ years of professional software engineering experience, preferably in full-stack, backend, platform, AI, automation, or product engineering roles. * Strong Python experience; additional experience with JavaScript/TypeScript, React, Node.js, FastAPI, Flask, or similar frameworks is an advantage. * Experience working with SQL and/or NoSQL databases, REST APIs, third-party integrations, and production systems. * Experience integrating LLM APIs, local models, AI agents, automation workflows, or AI-enabled internal tools is a strong advantage. * Experience with Git, CI/CD, cloud or on-prem deployment, Docker, Linux, monitoring, and debugging is preferred. * Experience writing technical documentation, implementation plans, and clear task breakdowns for both engineers and AI coding tools.
Main Responsibilities * Design, develop, and maintain AI-powered applications, internal tools, automation systems, and product features. * Translate product requirements and business problems into technical architecture, implementation plans, and working software. * Use AI coding assistants and agentic development tools to accelerate development while preserving quality, security, and maintainability. * Build integrations with LLMs, model APIs, vector databases, embeddings pipelines, data sources, and business systems. * Create prompts, context files, technical specifications, and development instructions that help AI tools produce accurate and maintainable results. * Review, test, debug, and refactor AI-generated and human-written code before production release. * Define evaluation methods, guardrails, and validation processes for AI-powered features. * Collaborate with product, R&D, QA, DevOps, and management to deliver reliable solutions end-to-end. * Continuously improve engineering workflows using modern AI-assisted development practices.
