Senior AI Engineer

Location: San Francisco, CA Experience: 5+ Years Employment Type: Full-Time Salary Range: $200,000 – $275,000 Base Salary + Bonus/Equity About the Role We are seeking a talented and experienced Senior AI Engineer to join our growing engineering team in San Francisco. In this role, you will design, develop, deploy, and optimize AI-powered applications and intelligent systems that solve complex business and customer problems. You will work closely with software engineers, machine learning engineers, data scientists, and product managers to take AI solutions from concept and experimentation through production. The ideal candidate has strong software engineering fundamentals, hands-on experience building production AI/ML systems, and a passion for emerging technologies such as Generative AI, Large Language Models (LLMs), and AI agents. This is an excellent opportunity for an engineer who enjoys working on challenging problems, building scalable AI products, and translating cutting-edge AI technologies into reliable real-world applications. Requirements Responsibilities Design, develop, and deploy production-grade AI and machine learning applications. Build and integrate AI/ML models, including LLMs and Generative AI solutions, into scalable products. Develop AI-powered features such as intelligent search, recommendation systems, conversational AI, automation, and agent-based workflows. Work with large and complex datasets to perform data preprocessing, feature engineering, model evaluation, and optimization. Develop and maintain machine learning and AI pipelines for training, inference, evaluation, and deployment. Fine-tune, evaluate, and optimize foundation models and LLMs for specific business use cases. Develop effective prompt engineering, retrieval-augmented generation (RAG), embeddings, vector search, and AI agent workflows. Build APIs and backend services that enable AI capabilities within production applications. Collaborate with software engineers, data scientists, product managers, and other technical stakeholders. Implement monitoring, observability, testing, and performance optimization for AI systems. Ensure AI applications are scalable, reliable, secure, and cost-effective. Stay current with emerging AI technologies, frameworks, research, and industry best practices. Contribute to technical architecture, design decisions, code reviews, and engineering standards. Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical field, or equivalent practical experience. 5+ years of professional experience in AI/ML engineering, machine learning engineering, software engineering, or a closely related field. Strong programming skills in Python and experience with modern software engineering practices. Strong experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn . Hands-on experience designing, building, deploying, and maintaining AI/ML systems in production. Strong understanding of machine learning concepts, model evaluation, experimentation, and optimization. Experience working with APIs, microservices, databases, and cloud-based applications. Experience with at least one major cloud platform such as AWS, GCP, or Azure . Strong understanding of software development practices including Git, testing, CI/CD, code reviews, and system design. Experience with production ML/AI pipelines and MLOps practices. Strong analytical, problem-solving, debugging, and communication skills. Ability to work effectively in a fast-paced, collaborative, cross-functional environment. Preferred Qualifications Hands-on experience with Large Language Models (LLMs), Generative AI, or AI agents . Experience with RAG architectures, vector databases, embeddings, and semantic search . Experience with LLM frameworks such as LangChain, LlamaIndex, or similar technologies . Experience with model fine-tuning, evaluation frameworks, inference optimization, or model serving. Experience with Kubernetes, Docker, Terraform, or other cloud-native technologies . Experience with distributed computing and data processing frameworks such as Apache Spark . Experience with SQL and NoSQL databases. Experience with vector databases such as Pinecone, Weaviate, Milvus, pgvector, or similar technologies. Experience building AI/ML APIs using frameworks such as FastAPI or similar. Experience with model monitoring, observability, performance optimization, and cost optimization. Experience with NLP, computer vision, recommendation systems, speech AI, or multimodal AI. Familiarity with responsible AI, model security, privacy, and AI governance practices. Technical Skills Languages: Python, SQL; familiarity with Java, Go, or C++ is a plus AI/ML: PyTorch, TensorFlow, Scikit-learn, Hugging Face, LLMs, Generative AI, NLP, Computer Vision GenAI: RAG, Prompt Engineering, Embeddings, Vector Search, AI Agents, Fine-Tuning, LLM Evaluation Cloud: AWS, GCP, or Azure Infrastructure: Docker, Kubernetes, CI/CD, Terraform Data: SQL, NoSQL, Spark, Data Pipelines MLOps: Model Deployment, Monitoring, Experiment Tracking, Model Serving, Performance Optimization Compensation & Benefits Base Salary: $200,000 – $275,000 , depending on experience, technical expertise, and qualifications. Competitive annual bonus and/or equity opportunities . Comprehensive medical, dental, and vision insurance. Generous paid time off and company holidays. 401(k) or retirement savings program. Professional development and learning opportunities. Access to modern AI/ML technologies and infrastructure. Collaborative, innovative, and high-growth engineering environment. Opportunity to work on high-impact AI products and next-generation technologies. Show more Show less