Founding AI Engineer (B2B SaaS Funded Startup - Remote Work)
Required skills
3–8 years of experience in ML/AI engineering or applied AI roles, Strong hands-on experience with LLMs (GPT, Llama, etc.), RAG architectures, Embeddings & vector databases, Experience building production-grade AI systems (not just prototypes), Strong programming skills in Python, Experience with FastAPI / Flask / async systems, Understanding of latency optimization, scaling, and cost trade-offs, Experience with data pipelines (PySpark, Airflow, etc.), Strong problem-solving and system design skills
Technologies
LLMs (GPT, Llama, etc.), RAG architectures, Embeddings & vector databases, FastAPI / Flask / async systems, PySpark, Airflow, vLLM, FastAPI, async pipelines, Kafka, vector databases, HNSW, hybrid search, reranking
Responsibilities
Design and build multi-agent systems that automate sourcing, screening, follow-ups, and candidate evaluation, Develop agent orchestration frameworks for complex, multi-step workflows, Build systems that can reason, act, and iterate autonomously, Build and optimize RAG pipelines over structured + unstructured data (resumes, job descriptions, conversations), Work with vector databases, embeddings, and retrieval strategies (HNSW, hybrid search, reranking), Improve grounding, reduce hallucinations, and enhance response quality, Optimize latency (TTFT), throughput, and cost for production systems, Work on model optimization, quantization, caching, and batching strategies, Build scalable inference systems using tools like vLLM, FastAPI, async pipelines, Design evaluation frameworks for retrieval + generation quality, Build feedback loops and telemetry pipelines to continuously improve model performance, Track metrics like accuracy, latency, hallucination rate, and user outcomes, Build ETL and data pipelines for ingestion, processing, and feature generation, Work with streaming systems (Kafka), batch systems, and real-time pipelines, Enable continuous learning and improvement of AI systems, Work closely with backend engineers to integrate AI systems into product workflows, Take ownership of systems from design → build → deploy → scale, Contribute to hiring, architecture decisions, and engineering culture
Seniority
3–8 years of experience
Domain
AI, Machine Learning, SaaS, Recruiting