AI Solutions Architect

eimagine seeks an AI Solutions Architect in Indianapolis, Indiana, to lead the design and delivery of scalable, enterprise-grade AI solutions for clients. The role combines technology strategy, software engineering, data science and machine learning to turn complex business challenges into practical solutions aligned with measurable business outcomes.

Responsibilities

• Translate ambiguous client needs into AI strategies and solution architectures; work with stakeholders to shape roadmaps, prioritize initiatives and connect technology decisions to business value.
• Lead end-to-end AI/ML solution design and guide implementation of data pipelines, model development workflows, production inference architectures, scalable model serving and distributed processing.
• Provide technical leadership to delivery teams, select suitable tools and cloud platforms, and establish standards for performance, reliability, scalability, security and governance.
• Assess system performance, model behavior and data pipelines to identify improvements. Guide responsible AI use, including explainability and risk mitigation; mentor engineers and turn emerging technologies into practical client recommendations.

Qualifications

• At least 5 years of experience in AI, machine learning or advanced analytics, with a track record of architecting and delivering enterprise solutions. Consulting or other client-facing experience and the ability to influence stakeholders are sought.
• Experience designing and deploying AI/ML solutions on Microsoft Azure, Amazon Web Services or Google Cloud; knowledge of scalable systems, distributed processing, PyTorch or TensorFlow, and production AI architectures.
• Experience integrating and operationalizing LLMs through APIs such as OpenAI, Azure OpenAI or Gemini; familiarity with enterprise retrieval-augmented generation and prompt engineering. A foundation in data architecture, pipelines and governance, DevOps/MLOps, CI/CD, Docker and Python is sought, along with problem-solving skills and the ability to guide engineering teams.
• A bachelor’s degree in information technology or computer science, or equivalent job-related experience, is required. Kubernetes experience is preferred; relevant Azure, AWS, GCP or AI certifications are a plus. The posting identifies the role as full-time but does not specify a role-specific work arrangement.