KodeKloud’s a fast-growing EdTech SaaS company dedicated to transforming the way businesses upskill their teams in DevOps, Cloud Computing, and IT. Our platform offers a hands-on, practical learning experience trusted by over 1 million users worldwide.
We at Kodekloud are committed to building a globally diverse team and are thrilled to extend employment opportunities to individuals in any part of the world. We require candidates to possess eligible working rights and have a compatible timezone overlap with their team to facilitate seamless collaboration.
As a remote-first company, our interviews and onboarding are entirely virtual, providing a smooth and efficient experience for our candidates.
Key Responsibilities
AI Product Development
- Design and develop AI-powered features for our e-learning platform, including the AI Assistant and new AI products
- Implement and optimize RAG (Retrieval-Augmented Generation) systems, including advanced Graph RAG architectures
- Build robust monitoring, tracing, and observability systems using LangSmith and other tools
- Integrate and fine-tune LLMs for educational use cases
- Create scalable APIs using Python and FastAPI to power AI features
Frontend Development
- Build responsive, intuitive interfaces for AI-powered learning experiences
- Develop real-time features using WebSockets and Server-Sent Events
- Ensure seamless integration between AI capabilities and user interfaces
Innovation & Optimization
- Identify opportunities to leverage AI for improving learning outcomes
- Rapidly prototype proof-of-concepts with cutting-edge AI tools
- Continuously optimize existing systems for performance and scalability
- Propose innovative solutions to enhance our AI Assistant's capabilities
Required Qualifications
Experience
- Minimum 5-10 years of full stack development experience
- At least 1 years working with AI/ML technologies in production
- Proven track record of delivering scalable applications serving large user bases
Must-Have Technical Skills
Backend & AI
- Python & FastAPI: Expert-level proficiency
- LangChain & LangGraph: Production experience building LLM applications
- RAG Systems: Deep experience with RAG implementations, including Graph RAG
- Vector Databases: Hands-on experience with Pinecone, ChromaDB, or similar
- LLM Platforms: OpenAI, Anthropic Claude, and Hugging Face integrations
- Fine-tuning LLMs: Knowledge of fine-tuning and deploying custom language models
- Monitoring & Observability:
- LangSmith for LLM application monitoring
- Prometheus & Grafana for metrics
- Google Cloud Monitoring
- Sentry for error tracking
Frontend
- JavaScript/TypeScript: Strong modern JavaScript proficiency
- Frameworks: Expert-level in at least one:
- React (with Next.js)
- Vue.js 3
- Styling: Tailwind CSS proficiency
- Real-time Communication: WebSockets and Server-Sent Events implementation
Infrastructure
- Cloud Platforms: GCP experience preferred, AWS/Azure acceptable
- Containerization: Docker and Kubernetes
- Databases: PostgreSQL, MongoDB
- Message Queue: Redis (preferred)
- Version Control: Git (GitHub/GitLab)
Essential Attributes
- Self-starter mentality with ability to drive projects independently
- Fast execution mindset - able to rapidly move from idea to implementation
- Strong problem-solving skills with systematic debugging approach
- Excellent communication skills for technical and non-technical audiences
- Passion for education technology and improving learning outcomes
Nice-to-Have Qualifications
- Contributions to open-source AI projects
- Experience with AI safety, alignment, and responsible AI practices
- Background in specific AI domains (NLP, Computer Vision, Speech Recognition)
- Experience in EdTech or e-learning platforms
- Knowledge of additional agent frameworks (CrewAI, AutoGen)
- DevOps/SRE/Networking experience
What We Offer
- Work on cutting-edge AI projects impacting millions of learners globally
- Flexibility to experiment with proof-of-concepts using the latest AI tools
- Access to state-of-the-art hardware and software resources
- Professional development budget for conferences, courses, and certifications
- Additional learning opportunities through KodeKloud's platform
- Collaborative environment with AI and education technology experts
- Competitive compensation
- Flexible work arrangements
Our Tech Stack
- Backend: Python, FastAPI
- AI/ML: LangChain, LangGraph, OpenAI, Anthropic, Pinecone, ChromaDB, Hugging Face
- Frontend: React/Vue.js, TypeScript, Tailwind CSS, Next.js
- Infrastructure: GCP (primary), Docker, Kubernetes, MongoDB, PostgreSQL, Redis
- Monitoring: LangSmith, Prometheus, Grafana, Sentry, Google Cloud Monitoring
- Version Control: Git, GitHub/GitLab
Join us in transforming how millions of people learn technology through the power of AI!
Originally posted on Himalayas
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