AI Content Systems Engineer
About the Role We are looking for an AI Content Systems Engineer to design, build, and scale intelligent systems that power the creation, validation, and optimization of technical content and assessments. This role sits at the intersection of AI engineering, developer tooling, and content systems , focusing on building automation pipelines, AI agents, and internal platforms that significantly enhance the efficiency, quality, and scalability of content generation workflows. You will work closely with content teams, engineers, and product stakeholders to develop AI-driven solutions for problem generation, evaluation, debugging, and continuous content improvement. Roles & Responsibilities Design and develop AI-powered content generation and validation systems for technical content function. Build and maintain LLM-based pipelines , prompt frameworks, and evaluation systems for content quality assurance. Develop agentic workflows for automated problem creation, test case generation, solution validation, and bug detection. Create scalable internal tools and platforms to streamline content operations and reduce manual effort. Integrate AI systems with assessment platforms, code execution environments, and data pipelines. Define and implement evaluation metrics for AI-generated content (accuracy, difficulty calibration, plagiarism, etc.). Collaborate with content engineers and SMEs to continuously improve system outputs and workflows. Debug, monitor, and optimize AI systems for performance, cost, and reliability. Drive experimentation with emerging AI techniques (RAG, fine-tuning, agents, multi-modal systems). Document system architectures, workflows, and best practices for internal adoption. Enable Content team to improve productivity and operation excellence with AI enabled workflows. Must-Have Skills Strong Programming Skills: Proficiency in Python (mandatory), and familiarity with JavaScript/TypeScript or Java. AI Coding & Developer Agents: Hands-on experience with tools like Claude Code, OpenAI Codex, GitHub Copilot, or similar AI-assisted development environments. AI-native IDEs & Productivity Tools: Experience using tools such as Cursor, Replit Ghostwriter, Codeium, or equivalent AI-first development environments. AI/ML & LLM Expertise: Strong understanding of transformer-based architectures such as Transformer architecture and familiarity with models like LLaMA, GPT-class models, or other open-source LLMs. AI Frameworks & Orchestration: Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar tooling. Core AI Domain Expertise: Strong foundation in Data Science, Machine Learning, Generative AI, and Agentic AI systems , including prompt engineering, RAG pipelines, embeddings, and evaluation techniques. System Design: Ability to design scalable systems, pipelines, and APIs. Data Structures & Algorithms: Strong problem-solving fundamentals. Backend Development: Experience building services, APIs, and distributed systems. Cloud & Infra: Familiarity with AWS/Azure, containers, and deployment workflows. Databases: Working knowledge of SQL and NoSQL systems. Debugging & Evaluation: Ability to analyze AI outputs and improve system performance. Good-to-Have Skills Experience with RAG pipelines, vector databases, and embeddings . Exposure to fine-tuning, model evaluation frameworks, and guardrails . Familiarity with multi-agent systems and autonomous workflows . Experience building developer tools, internal platforms, or automation systems . Understanding of technical assessment ecosystems or ed-tech platforms . Contributions to open-source AI tools or experimentation with emerging models . What You’ll Build / Own AI systems for automated question generation and validation Code-debugging and evaluation engines for large-scale assessments Internal tools for content operations, analytics, and workflow automation Scalable pipelines for continuous content improvement and auditing Leveraging current platform to have broad Technical skill assessment capabilities Who You Are A systems thinker who enjoys building end-to-end AI solutions , not just models Someone who thrives in 0 → 1 problem spaces and fast-paced environments Passionate about AI, developer ecosystems, and scalable automation Detail-oriented with a strong focus on quality, reliability, and impact How to Apply: (Strictly apply through LinkedIn. DMs will not be seen or responded to) Apply now and be part of an exciting journey at HackerEarth.