New

Full Stack AI Engineer

Spectraforce Technologies
United States, California, Sunnyvale
Apr 02, 2026
Title- Full Stack AI Engineer Duration - 12 Months Location - Sunnyvale CA 94085 ( Hybrid - come onsite as needed) We are seeking a highly skilled Founding AI Engineer to partner with internal and cross-functional teams in defining AI product features, scope, and the platform's technical foundation. Key Responsibilities: Serve as a Founding AI Engineer, collaborating with cross-functional teams to define AI product features, scope, and overall technical architecture. Design and implement generative AI systems, including: Multi-agent workflows LLM orchestration patterns Tool-calling architectures MCP integrations to connect models with enterprise APIs, tools, and data systems Build scalable AI data pipelines to ingest heterogeneous data sources and implement AI-driven ETL processes, including: Data cleaning Normalization Deduplication Structured storage in production databases and vector indexes Develop and optimize GenAI systems, including: Fine-tuning LLMs and transformer models (e.g., LoRA/PEFT) Prompt engineering Designing RAG architectures for knowledge retrieval Train, test, and deploy machine learning models, building: Low-latency inference pipelines Scalable AI services for real-time and batch workloads Develop backend services and AI product interfaces, including: APIs Microservices AI-powered dashboards Ensure production reliability through: Monitoring Autoscaling Performance optimization Minimum Qualifications: Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field 5+ years of experience building production AI or machine learning systems Hands-on experience developing GenAI / LLM-powered applications using models such as GPT, Claude, or Gemini Experience designing and deploying: Agentic AI systems MCP integrations LLM orchestration workflows Experience building: RAG systems Vector search solutions AI knowledge discovery platforms Experience with ML frameworks such as: PyTorch TensorFlow scikit-learn Experience designing scalable data pipelines and AI-driven ETL workflows Experience building AI-powered dashboards or knowledge discovery interfaces Preferred Qualifications: Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field Experience fine-tuning transformer models using techniques such as LoRA or PEFT Hands-on experience with: Cloud platforms (e.g., AWS) Containerization technologies (e.g., Docker)