Senior AI Engineer

Optimal Dynamics-posted 3 months ago
Full-time • Senior
New York City, NY
51-100 employees
Publishing Industries
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We're looking for a Senior AI Engineer to lead the 0→1 buildout and 1→n scaling of AI capabilities at Optimal Dynamics. You'll set direction, establish engineering standards, and deliver production systems that ground AI outputs in trustworthy company and customer data. This is a hands-on role with broad ownership where you'll make key architecture and tooling choices and evolve them as we learn.

  • Own RAG initiatives end-to-end from problem framing and data readiness through prototyping, iteration, and production launch.
  • Establish foundational components and practices for document processing, indexing, retrieval, orchestration, and evaluation; selecting tools and approaches that balance quality, cost, and speed.
  • Build reliable services and APIs that are observable, secure, and designed for scale in a cloud environment.
  • Define success metrics (quality, latency, cost, safety) and drive continuous improvement via experimentation and data-driven decisions.
  • Create durable team assets (i.e. playbooks, test harnesses, checklists, and documentation) to make RAG development repeatable across products.
  • Collaborate cross-functionally with Product, Data/ML, Engineering, and GTM to translate ambiguous needs into shippable capabilities with clear business impact.
  • Mentor teammates and contribute to a strong engineering culture around AI systems and responsible deployment.
  • 4+ years of proven industry experience building and operating backend, platform, or data services at production scale
  • Bachelor's degree in Computer Science, Electrical Engineering, Operations Research, or Mathematics/Physics
  • Proven track record delivering data or ML-powered features end-to-end (Discovery/Prototyping > Launch > Iteration).
  • Python Proficiency - you write well-tested & maintainable code.
  • API design expertise and experience with cloud services (preferably AWS)
  • Familiarity with information retrieval concepts and grounding AI systems in trustworthy data.
  • Comfort setting technical direction, selecting tools, and establishing engineering best practices for AI-focused builds.
  • Experience introducing retrieval-augmented or knowledge-grounded AI capabilities in a product or platform context.
  • Exposure to evaluation methodologies for AI systems (quality, latency, cost, safety) and running experiments/A-B tests.
  • Background working with unstructured data pipelines, indexing, and search, whether homegrown or via managed services.
  • Experience mentoring engineers, uplifting practices, and creating reusable playbooks and templates.
  • Experience in the transportation, logistics, or broader supply chain industry.
  • Customer-facing collaboration comfort: gathering requirements, scoping MVPs, and measuring ROI post-launch.
  • Work with a world-class AI team and industry experts.
  • Opportunity to shape a greenfield capability from the ground up.
  • Pragmatic, collaborative culture with tight feedback loops.
  • Autonomy to choose the right tools.
  • Support to make bold ideas a reality.
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