Senior AI Systems Engineer

Job Role: Senior AI Systems Engineer

Location: San Francisco, CA (Onsite)

Role Overview

Value Technology is seeking a high-impact Senior AI Systems Engineer to lead the design and deployment of next-generation agentic AI solutions. This role requires a sophisticated understanding of Generative AI architectures, including Retrieval-Augmented Generation (RAG) and multi-agent orchestration. You will be responsible for moving beyond simple chat interfaces to building production-grade "AI teammates" that automate complex, real-world workflows.

Key Responsibilities

• Agentic Orchestration: Design and implement complex agentic workflows—including Sequential, Parallel, and Loop patterns—to handle multi-step reasoning and autonomous execution.
• System Architecture: Architect and deploy secure, scalable microservices using FastAPI and Node.js to serve AI features to production environments.
• RAG Pipeline Optimization: Develop and refine RAG pipelines by optimizing document store chunking, vector embedding strategies, and prompt engineering to minimize hallucinations and maximize accuracy.
• Infrastructure & GitOps: Manage cloud-native resources and CI/CD pipelines using Terraform, Kubernetes, and GitHub Actions to automate the deployment and rollback of AI services.
• Cross-Functional Leadership: Collaborate with product owners and infrastructure teams to integrate conversational AI and predictive models (e.g., Meta Prophet) into enterprise workflows.

Minimum Qualifications

• Experience: Minimum of 5–6 years of professional software engineering experience, with at least 2 years focused on Generative AI and Large Language Model (LLM) integration.
• Education: Bachelor’s or Master’s degree in Mathematics, Computer Science, or a related quantitative field.
• AI Expertise: Deep hands-on experience with agentic frameworks such as LangGraph, CrewAI, LangChain, or Google ADK.

Technical Stack:

• Proficiency in Python (FastAPI, Pandas, PyTorch) and Java
• Strong experience with cloud platforms (AWS/Google Cloud Platform/Azure) and containerization (Docker/Kubernetes).
• Expertise in SQL and NoSQL databases, including PostgreSQL, MongoDB, and Amazon DynamoDB.
• Problem Solving: Proven ability to analyze and solve complex technical problems, ensuring the robustness and scalability of AI-driven solutions.

Preferred Skills

• Experience building voice-enabled AI solutions or multimodal agent flows using Pipecat.
• Background in financial services or medical staffing sectors, with a focus on data security and regulatory compliance.
• Familiarity with Model Context Protocol (MCP) and building custom tools for AI assistants.