Platform Engineer, AI | $250k

Feldspar & Flint LLC is a Recruiting & Staffing firm that specializes in operational strategy across core business functions.

Build and advance an enterprise AI platform that enables secure, production-grade AI applications, agents, automation, and reusable services across investment and corporate functions. This role combines backend engineering, Generative AI, and platform architecture with meaningful influence on how AI is adopted across the organization.

Responsibilities

• Design and deploy production AI applications powered by leading foundation models and modern Generative AI technologies.
• Build reusable AI platform services, including MCP servers that securely connect enterprise tools, APIs, and data.
• Develop intelligent agents that can plan, reason, and execute complex workflows across business functions.
• Create Retrieval-Augmented Generation solutions using enterprise knowledge sources, embeddings, and vector databases.
• Engineer scalable backend services and secure integrations using Java/Spring Boot, Python, and RESTful APIs.
• Establish evaluation, observability, prompt testing, monitoring, governance, and cost-management practices for AI solutions.
• Partner with business and technical stakeholders to identify, prioritize, and deliver high-value AI capabilities.
• Shape platform architecture, mentor engineers, contribute to technical design and code reviews, and document development and operational standards.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical discipline, plus 5+ years of professional software engineering experience building scalable backend applications.
• Strong proficiency in Java/Spring Boot and/or Python, with experience developing REST APIs, SQL-based applications, distributed systems, Git, Docker, and Kubernetes.
• Hands-on experience delivering production Generative AI solutions using LLMs, with practical knowledge of RAG, embeddings, vector databases, AI agents, and modern AI development frameworks.
• Experience with one or more cloud AI ecosystems such as Azure AI, AWS Bedrock, Google Vertex AI, or comparable platforms.
• Ability to work effectively across technical and business teams, applying strong analytical, problem-solving, communication, and collaboration skills in an Agile environment.
• Exposure to enterprise AI platforms, reusable AI services, MCP, AI governance, enterprise search, workflow automation, financial services, or related technologies is advantageous but not required.