Job Description

Requirements:

• 4 years of experience as a fullstack or backend engineer
• Strong proficiency in Python and JavaScript/TypeScript
• Experience with FastAPI / Django / Node.js and React / Next.js
• Solid understanding of distributed systems and async architectures
• Hands-on experience deploying LLMs such as GPT-4/4.1, Claude, LLaMA, Mistral, Mixtral
• Experience serving models using vLLM, Triton, TGI, or similar frameworks
• Strong understanding of transformer models and inference trade-offs
• Experience with embeddings, vector search, and RAG architectures
• Experience with AWS, GCP, or Azure (GPU workloads preferred)
• Strong Docker and Kubernetes experience
• Familiarity with CI/CD pipelines for ML systems
• Experience with observability tools (Prometheus, Grafana, OpenTelemetry)
• Experience with multimodal AI (audio, video, image models)
• Experience optimizing LLM inference costs at scale
• Startup or high-growth environment experience
• Prior work on AI-first or AI-native products

Responsibilities:

• Deploy and optimize LLMs (open-source and commercial) for production use
• Implement inference optimization techniques (quantization, batching, caching, distillation)
• Build and maintain RAG pipelines (embeddings, vector databases, retrieval strategies)
• Evaluate and improve model quality (latency, accuracy, hallucination reduction, cost)
• Implement prompt management, versioning, and A/B testing
• Design and develop scalable APIs for AI-driven features
• Deploy and manage model-serving infrastructure (Docker, Kubernetes, GPUs)
• Optimize hardware utilization for inference workloads
• Implement monitoring, logging, and alerting for AI services
• Ensure security, data privacy, and compliance across AI pipelines
• Build internal tools and user-facing interfaces for AI workflows
• Integrate LLM services into web and mobile applications
• Work closely onsite with product managers, designers, and data teams
• Rapidly prototype, test, and iterate on AI-powered features