Senior AI Engineer

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🔥 39 minutes ago

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NovoEd

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2012

📚 Education

☁️ SaaS

👥 HR Tech

Education • SaaS • HR Tech

NovoEd is an AI-enabled talent development platform designed to enhance employee training and organizational effectiveness. It focuses on providing customizable learning experiences that drive leadership development, employee onboarding, and functional upskilling through innovative tools and technologies. With a commitment to building future-ready talent, NovoEd offers a comprehensive solution for enterprises and training providers to transform their workforce and achieve measurable business outcomes.

📋 Description

• Design, develop, and deploy production-grade AI-powered backend systems. • Integrate LLMs and traditional ML models into performant, scalable architectures. • Integrate and optimize vector databases for retrieval-augmented generation (RAG) pipelines and other traditional ML queries. • Write clean, well-structured, and testable Python code following best practices. • Capable of thinking about performance and ensuring optimal decision making to reduce latency. • Build hybrid architectures that balance LLM calls with traditional ML. • Debug complex, cross-layer issues spanning backend, AI inference, and UI integration. • Conduct thorough dev testing before QA handoff to ensure production reliability. • Collaborate with product, backend, and frontend engineers to deliver cohesive solutions.

🎯 Requirements

• 3–5+ years professional backend engineering experience in Python, FastAPI or Flask, and background processing. • Proven record of deploying Python applications to production (not just scripts or academic work). • Strong grasp of software design patterns. • Strong understanding of backend performance, parallel processing in background jobs and multi-threading. • Proficiency in performance tuning specially for heavy AI models. • Applied machine learning experience — training, evaluating, and maintaining small task-specific models. • Familiarity with LLM integration, prompt engineering, and context window optimization. • Proven ability to debug AI behavior, identify root causes, and make targeted fixes. • Strong testing discipline for both backend and AI components. • Experience with background processing with Celery or other major libraries. • Experience with monitoring APIs and background processing. • Experience with ensuring visibility and error reporting. • Nice to have: experience with Docker, understanding of CI/D, deployment automation and Kubernetes.

🏖️ Benefits

• Direct impact on the company’s competitive edge. • Small, fast-moving team with high autonomy. • Work on practical, real-world AI applications — not just research. • Opportunity to shape our AI architecture and best practices from the ground up.