Senior AI Backend Engineer & Instructor

Senior AI Backend Engineer & InstructorCompany: Techvruk   Location: Remote Engagement: Part-time / Contract / Full-timeExperience: 4+ yearsAbout Techvruk & The RoleTechvruk builds industry-focused technology programs that help students, fresh graduates, and early-career engineers become job-ready. We're launching an AI Backend Engineer program to teach learners how to build real-world backend and AI applications, from fundamentals to production deployment — and we need a Senior AI Backend Engineer & Instructor to help build and teach it.This is not a traditional classroom-trainer role. You'll design curriculum, create practical learning content, run sessions, and mentor students through real projects — teaching how software is actually built in industry. The goal: move students from “I know Python and basic programming” to “I can build and deploy a production-ready AI backend application.”What You'll DoBuild the curriculum — help decide what students learn first, how it progresses beginner → advanced, and what skills companies actually expect from junior AI/backend engineers.Teach backend engineering — Python, Fast API, REST APIs, PostgreSQL/SQL, SQL Alchemy, auth & API security, async programming, error handling, testing, Git/GitHub, Docker — with emphasis on concepts, not just frameworks.Teach AI application development — LLM fundamentals, Open AI/Gemini/Anthropic APIs, prompt engineering, embeddings, vector databases, RAG, Lang Chain/Llama Index, tool calling, AI agents, structured outputs, and building AI APIs with Fast API.Teach production engineering — cloud deployment (AWS/Azure/GCP), CI/CD, Redis, background jobs, logging, monitoring, performance, security, scalability, and production debugging.Mentor students — debug and review code, explain difficult concepts, build confidence, prepare them for technical interviews, and guide hands-on projects mirroring real industry work: a production REST API, an AI/RAG application, and a final end-to-end capstone (frontend → API → database → AI/LLM → RAG → background jobs → Docker → cloud → monitoring).Who You'll TeachEngineering students, final-year students, fresh graduates, early-career (0–2 yr) software engineers, and Python developers moving into AI.What We're Looking ForMust Have4+ years of professional software engineering experienceStrong Python backend development experienceExperience with Fast API, Django, Flask, or similar frameworksStrong SQL/PostgreSQL knowledge; experience designing and building REST APIsExperience with Docker and GitPractical experience building AI/LLM-powered applicationsUnderstanding of RAG, embeddings, vector databases, or AI agentsExperience deploying applications to a cloud platformTeaching / Mentoring (valued equally with technical skills)Ability to explain complex concepts simply, run live coding sessions, debug while teaching, create practical assignments, give constructive code reviews, and mentor patiently.Previous formal teaching experience is not required — if you're a strong engineer who regularly mentors juniors or runs internal technical sessions, we'd love to hear from you.A strong candidate can take a question like “What is RAG?” and walk a Python developer who's never built an AI app through Problem → Architecture → Code → Database → Retrieval → LLM → API → Deployment.Bonus SkillsLang Chain, Llama Index, Open AI, Gemini, Anthropic, pg vector, Pinecone, Qdrant, Redis, Celery, Kafka, AWS, Azure, Kubernetes, CI/CD, AI SaaS products — plus technical blogging, YouTube, public speaking, workshops, or prior mentoring experience.Why Join Techvruk?Help build a career-focused AI engineering program from the ground up: shape the curriculum, mentor the next generation of developers, work with modern AI and backend technologies, build your reputation as a technical educator, and potentially grow into a long-term mentor/instructor role with Techvruk.How to ApplyPlease share: your resume/LinkedIn, GitHub or portfolio (if available), a brief summary of your backend and AI experience, previous mentoring/training experience (if any), and links to technical content, talks, or workshops (if available).