Posted:3 hours ago|
Platform:
Work from Office
Full Time
We are building GenAI-driven assistants to transform how professionals learn, buy, and get support. Youll work closely with the CTO and lead the architecture, development, and deployment of LLM-powered solutionsincluding custom model training on proprietary datasets, RAG pipelines, and multi-agent systems. This is a full-stack AI role—you’ll also drive infrastructure, DevOps, and observability across the GenAI stack to ensure production-grade performance, scalability, and automation.
LLM fine-tuning and custom model creation using proprietary data (e.g., SFT, LoRA, PEFT)
Strong expertise in RAG architectures, vector stores (Pinecone, FAISS), and embeddings
Hands-on with LangChain, LangGraph, and prompt engineering
Solid cloud experience (AWS – ECS, Lambda, Bedrock, S3, IAM)
Backend/API engineering (FastAPI or Node.js), Docker, Git, CI/CD (GitHub Actions, CodePipeline)
Scripting with Python & Bash; n8n or other workflow automation tools
Observability: Langfuse, LangWatch, OpenTelemetry Bonus Skills
Agentic frameworks (LangFlow, CrewAI, AutoGen)
Experience integrating chatbots in web or LMS environments
Infra as Code (Terraform), monitoring tools (Grafana, CloudWatch)
Designing and scaling AI-first features for real users
Leading AI engineering practices end-to-end—model, infra, and app layer
Rapid experimentation, iteration, and optimization
Collaborating cross-functionally and shipping production-grade solutions fast
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