Finn Partners-posted 3 days ago
$90,000 - $100,000/Yr
Full-time • Mid Level
Remote • New York, NY
1,001-5,000 employees

The AI Solutions Engineer is the primary builder, architect, and technical steward of the organization's internal AI capabilities. This role is responsible for the design, development, and operationalization of robust, scalable AI-powered tools and integrations that solve specific business problems. Their mission is to translate high-level business needs and identified opportunities into tangible, working technology. The primary objective is to build and maintain the technical infrastructure that enables the organization's AI adoption strategy. Key Responsibilities: This role is responsible for the full technical lifecycle of AI-driven solutions, from initial prototype to production deployment and maintenance. Platform Assessment & Implementation · Leverage first, build second: Prioritize the use of AI capabilities already available within FINN Partners' tech stack to automate workflows and boost productivity. · Assess, evaluate, and implement a standard agentic AI platform to serve as the foundational technology for enterprise-wide solutions, ensuring our internal AI stack remains modern, efficient, and aligned with industry best practices. Internal Tool Development & Prototyping · Design, build and maintain supplementary internal tools, integrations and micro‑services when native capabilities do not fully address identified pain‑points or scalability requirements. · Rapidly prototype lightweight AI‑enabled utilities, validate business value, and promote successful pilots into robust production services. · Oversee architectural and technology choices made by AI systems by reviewing model selection, libraries and frameworks, and debug complex multi‑service environments when needed. System Architecture & Technical Oversight · Oversee architectural and technology choices for all internal AI systems by reviewing model selection, libraries, and frameworks. · The Solutions Engineer is also responsible for debugging multi-service environments when needed. Hands-On Prompt Engineering & Solutioning · Provide expert guidance on crafting effective prompts and interaction patterns for generative models (Gemini, ChatGPT, Claude, etc.). · Assist teams with data preparation, fine‑tuning and evaluation to maximize solution accuracy, safety and reliability.

  • Design, development, and operationalization of robust, scalable AI-powered tools and integrations
  • Translate high-level business needs and identified opportunities into tangible, working technology
  • Build and maintain the technical infrastructure that enables the organization's AI adoption strategy
  • Full technical lifecycle of AI-driven solutions, from initial prototype to production deployment and maintenance
  • Assess, evaluate, and implement a standard agentic AI platform
  • Design, build and maintain supplementary internal tools, integrations and micro‑services
  • Rapidly prototype lightweight AI‑enabled utilities, validate business value, and promote successful pilots into robust production services
  • Oversee architectural and technology choices made by AI systems
  • Debugging multi-service environments
  • Provide expert guidance on crafting effective prompts and interaction patterns for generative models
  • Assist teams with data preparation, fine‑tuning and evaluation
  • A solid understanding of machine learning techniques and algorithms.
  • Strong proficiency in applicable programming languages
  • Experience with AI frameworks and libraries
  • Practical experience with generative AI APIs and evaluation methods.
  • Strong familiarity with cloud platforms like Azure, GCP, or AWS and their respective AI/ML services. The ability to design and implement scalable and robust AI systems is a core requirement.
  • Familiarity and experience with setting up and leveraging MCP servers to power AI driven actions
  • Strong analytical thinking and problem-solving capabilities are essential for navigating complex technical challenges and translating business needs into technical requirements.
  • A degree in Computer Science, Artificial Intelligence, or a related field is typically required, along with significant hands-on experience in a similar role.
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