Senior AI Platform Engineer

Blackbaud

4d•$117,200 - $157,500

About The Position

Blackbaud is seeking a Senior AI Platform Engineer to design, build, deploy, and support enterprise AI solutions and the platform capabilities that enable them. This hands-on software engineering role focuses on enabling AI tools that transform business processes. The engineer will build agentic and LLM-powered solutions while establishing reusable engineering patterns, security controls, observability, and operational practices for safe and effective enterprise-scale AI adoption.

Requirements

At least 5 years of professional software engineering experience building, delivering, and supporting production software.
Hands-on experience delivering LLM-powered or generative AI solutions into production, beyond prototypes or demonstrations.
Experience building agentic AI solutions, including tool or function calling, RAG, orchestration, multi-step workflows, or autonomous or semi-autonomous execution.
Experience implementing AI observability, evaluation, and monitoring, with an understanding of hallucination, output quality, drift, latency, usage, and cost.
Strong understanding of enterprise security concepts, including authentication, authorization, least privilege, sensitive-data protection, secrets management, and auditability.
Experience integrating applications with enterprise APIs, data sources, identity systems, and cloud services.
Experience with Claude in an enterprise or administrative context, such as enterprise access and administration, permissions, integrations or connectors, governance, usage monitoring, or solutions built using Claude.
Strong experience with modern software engineering practices, including APIs, automated testing, CI/CD, telemetry, and production support.
Ability to evaluate tradeoffs across model capability, security, reliability, performance, maintainability, and cost.
Strong collaboration and communication skills, including the ability to work across engineering, architecture, data, security, and business teams.

Responsibilities

Design, build, test, deploy, and support production agentic and LLM-powered solutions that integrate with enterprise data, APIs, tools, and workflows.
Build reusable AI platform services, integration patterns, guardrails, and reference implementations to enable secure and efficient AI adoption.
Design security controls for AI agents, including identity, authorization, least-privilege access, sensitive-data handling, auditability, and secure integrations.
Implement AI-specific observability and evaluation, monitoring output quality, hallucinations, behavioral or model drift, failures, latency, token consumption, and cost.
Develop mechanisms to detect, troubleshoot, contain, and remediate unexpected or unsafe agent behavior.
Optimize model selection, context management, agent workflows, and consumption to balance quality, reliability, performance, and cost.
Apply software engineering practices including automated testing, CI/CD, telemetry, code review, secure development, and production support.
Partner with Enterprise Architecture and Data Platform teams to establish scalable integration patterns, data access approaches, and technical standards for enterprise AI.
Collaborate with business stakeholders and the Product AI Platform team to understand use cases, share platform patterns and learnings, and translate enterprise needs into reliable AI capabilities.
Evaluate emerging AI models, agent frameworks, protocols, and platforms and help establish practical standards and reusable approaches for enterprise adoption.
Mentor other engineers and contribute to a strong engineering culture around AI development and operations.