Senior AI/ML Engineer

Project Overview We are building a Live AI Business Knowledge platform powered by ethically sourced, structured, and continuously evolving data. You will work with a stealth-stage startup where your architectural decisions directly shape core AI infrastructure, agent design, and long-term system scalability. We are seeking a Senior AI/ML Engineer for an independent contractor engagement to design and implement AI agents, retrieval-augmented generation (RAG) infrastructure, and supporting knowledge systems. Engagement Structure & Compensation • Engagement Type: Independent Contractor • Compensation: $3,000/month contractor engagement + meaningful equity participation • Duration: 3 months (starting March 2026) with an extension possible based on project progress and mutual interest. • Time Commitment: ~25–30 hours/week (milestone-based, self-scheduled) Equity participation will be structured as Non-Qualified Stock Options (NSOs) and aligned to scope, experience, and milestone ownership. All grants are subject to Board approval. This engagement is structured for senior engineers who enjoy building early platform infrastructure, working in startup environments, and participating in meaningful equity upside while contributing to real product development. Applicants must be authorized to work in the United States without employer sponsorship. This role does not provide visa sponsorship. What You'll Work On You will architect and ship: • Production-grade AI/ML systems for knowledge extraction and reasoning • Retrieval-Augmented Generation (RAG) pipelines with embedding workflows and vector databases • Data ingestion, normalization, and transformation pipelines for large-scale knowledge systems • AI agent orchestration frameworks and multi-agent coordination workflows • Model evaluation, observability, and governance systems • Scalable inference infrastructure integrated with backend product APIs • Latency- and cost-optimized production deployment strategies Deliverables are milestone-defined and executed in structured architectural phases. Required Experience: Must Have • 7+ years of professional experience in applied AI/ML or production machine learning systems • Demonstrated experience shipping and operating AI systems in production environments • Strong expertise in designing production LLM systems, including Retrieval-Augmented Generation (RAG), embedding pipelines, and retrieval optimization. • Embeddings and vector database architectures • Python-based ML tooling and API integration • Ability to evaluate architectural tradeoffs across latency, reliability, cost, and scalability Preferred • Knowledge graphs or graph databases • Multi-agent systems or orchestration frameworks • AI safety, compliance, or sensitive-data handling • Early-stage startup or platform-build experience Ideal Engagement Fit This engagement is a strong fit for senior practitioners who enjoy building foundational AI infrastructure, prefer milestone-based delivery, and are comfortable owning end-to-end architecture decisions. You can reason about system tradeoffs, operate with minimal supervision, and clearly articulate design decisions. This is not a salaried W-2 role and is not structured for hourly optimization. How We Work This is a contractor engagement. You determine how the work is performed, use your own tools and equipment, manage your own schedule to meet agreed milestones, and handle your own taxes and expenses. Collaboration is async-friendly with structured architecture reviews and integration discussions as needed. We are seeking senior engineers comfortable operating in an environment of ownership, ambiguity, and high accountability.