Agentic AI Framework Engineer (LLM & Automation)

Primary Skills: Agentic AI framework, Foundational Models, Python, Startup Background/Mindset Location: San Jose, CA (Hybrid, San Jose preferred; open to San Francisco, CA and open to remote candidates) Duration: 1 month, potential to extend or covert to FTE Contract Type: W2 only Job Summary Join our team to build a next-generation agentic AI framework that translates conversational inputs (via LLMs) into automated workflows, orchestrating tasks like scheduling, video recording, and social media posting. Using foundational models (no fine-tuning required), you’ll design a scalable, modular backend system integrating APIs, RPA, and microservices, ensuring low-latency performance and robust security. Responsibilities • Develop a scalable backend framework to translate conversational instructions into automated tasks using microservices, APIs, and RPA • Integrate LLMs to parse user intent, extract tasks, and dynamically plan workflows • Architect modular, extensible systems to support new services and integrations without refactoring • Optimize LLM inference and agent operations for low latency and high availability • Manage API integrations (e.g., social platforms, calendars) and web-based tasks via RPA or headless browsers • Implement data security, governance, and compliance best practices • Collaborate with frontend, DevOps, and product teams to define architecture and deliver solutions • Build monitoring and analytics for automation performance and system metrics Required Skills and Qualifications • Bachelor’s degree or higher in Computer Science or related field • Proven experience building agent-based frameworks (e.g., LangChain) for multi-step workflows • Extensive experience deploying LLMs in production, optimizing for low-latency inference • 5+ years developing high-performance backend systems (Python, Go, Java, or Node.js) • Proficiency with REST, GraphQL, or gRPC, and integrating complex APIs (e.g., social media, scheduling) • Experience with RPA tools, headless browsers, or web scraping for dynamic sites • Expertise in microservices, cloud platforms (AWS, Azure, or GCP), and containerization (Docker/Kubernetes) • Strong systems architecture skills for modular, distributed designs • Comfortable in fast-paced, agile environments with evolving priorities