Job Title: Computer Scientist Location: San Jose, CA (This is a Hybrid role. Highly preferred San Jose office location. Also open to San Francisco) Duration: 1 month. Contract Type: W2 only Pay Rate: $105.62/Hour Job Description About the Role: We’re looking for an experienced Backend Engineer to join our Client as a Computer Scientist (Level 3/4) and spearhead the development of a next-generation agentic automation framework . This framework will ingest a conversation (via NLP/LLMs) where strategies and tactics are agreed upon, and autonomously translate those agreements into automated workflows. For example, if the conversation concludes that a user needs to schedule a weekly video recording session and subsequently post the videos on Instagram, our framework should: • Recognize the need to schedule a weekly time slot. • Send a calendar invite to the user. • Facilitate video recording. • Connect to Instagram’s API or web interface. • Schedule the posts. • Monitor analytics to measure performance. All of these steps must be orchestrated seamlessly through APIs, virtual browser sessions (RPA), and external service integrations. The right candidate will bring an in-depth understanding of agent-based architectures, advanced knowledge of LLM deployments, and the ability to build a robust, modular, and extensible automation framework from the ground up. Key Responsibilities • Design & Develop : Build a scalable backend automation framework that can translate conversational instructions into actionable tasks and orchestrate them using microservices, external APIs, scrapers, and RPA/VMs. • LLM Integration : Work closely with conversational AI and LLMs (e.g., GPT-like models) to parse user intent, extract tasks, and dynamically plan automation flows. • Modular Extensibility : Architect the framework to accommodate new services, APIs, or integrations without major refactoring - ensuring reusability and maintainability. • Performance Optimization : Ensure ultra-low latency and high availability of LLM-driven services in production, optimizing inference pipelines and agent operations. • API & RPA Coordination : Integrate diverse APIs (social platforms, calendars, CRMs, etc.), and manage web-based tasks via RPA or VM-based strategies to replicate human browser actions where no direct API is available. • Security & Compliance : Implement best practices around data security, governance, and compliance, ensuring sensitive user data and credentials are properly managed and protected. • Collaboration : Partner with frontend, DevOps, data scientists, and product teams to shape technical architecture, define roadmaps, and ensure smooth cross-functional delivery. • Monitoring & Analytics : Develop monitoring and logging solutions that give visibility into automation flows, success/failure rates, and system performance metrics. Required Qualifications • Bachelors Degree or higher in Computer Science or related fields. • Agentic Framework Mastery : Proven track record with agent-based frameworks (e.g., LangChain or similar) to dynamically plan and orchestrate multi-step workflows. • LLM Production Experience : Extensive experience deploying and operating LLM models in production environments, ensuring low-latency inference and scalable infrastructure (e.g., GPU/CPU optimization, container orchestration, etc.). • Backend Engineering Excellence : 5+ years of software development experience building high-performance backend systems in languages like Python, Go, Java, or Node.js. • API Design & Integration : Deep familiarity with REST, GraphQL, or gRPC, plus hands-on work integrating complex external APIs (including social media platforms and scheduling services). • RPA / Virtual Browsers : Proficiency with RPA tools, virtual machines, headless browsers, or similar methods for web automation when APIs are limited or unavailable. • Scraping & Data Processing : Solid experience with web scraping libraries or frameworks, ensuring robust handling of dynamic or JS-driven sites. • Microservices & Cloud : Experience designing and deploying microservices in a modern cloud environment (AWS, Azure, or GCP), including containerization (Docker/Kubernetes) and CI/CD pipelines. • Systems Architecture : Ability to architect large-scale, distributed systems with a focus on modular, extensible designs. • Agile Mindset : Comfortable working in a fast-paced, iterative environment, adapting to evolving priorities and technologies.