AI Solutions Architect

Overview

At eimagine, we know that your best work happens when you live your best life and share your unique talents, so we do everything we can to be intentional in a remote enabled environment to make that possible. Recognized as a Best Places to Work since 2015, we are a team of humbly confident people who are proud of their craft, continuous learners, and have been known to cheer loudly for our teammates. For over 25 years we have been helping clients navigate technology and business change, while staying committed to delivering value & outcomes that enables their success.

Due to continued growth, we are seeking an AI Solutions Architect to lead the design and delivery of scalable, enterprise-grade AI solutions that solve complex business challenges for our clients. This role operates at the intersection of technology and strategy—bringing together software engineering, data science, and machine learning to architect solutions that are not only technically sound but aligned to business outcomes. As a senior leader, you will guide clients through ambiguity, shape AI strategies, and ensure solutions are built for scale, sustainability, and measurable impact.

You will play a critical role in translating emerging AI capabilities into practical, high-value applications. If you’re passionate about turning emerging technologies into real-world solutions and want to partner with clients to create meaningful business value, this could be your next step. Join us as we #eimaginebetter.

• Bachelor’s degree in information technology, computer science or equivalent job-related experience required.

• 5+ years of experience in AI, machine learning, or advanced analytics, with a strong track record in architecting and delivering enterprise solutions
• Proven experience in a consulting or client-facing role, with the ability to influence stakeholders and drive strategic conversations
• Deep experience designing and deploying AI/ML solutions in cloud environments such as Microsoft Azure, Amazon Web Services, or Google Cloud
• Strong understanding of scalable system design, distributed processing, and production-grade AI architectures
• Experience with modern ML frameworks such as PyTorch, TensorFlow, or similar tools
• Experience integrating and operationalizing large language models (LLMs), including APIs such as OpenAI, Azure OpenAI, or Gemini
• Familiarity with generative AI patterns such as retrieval-augmented generation (RAG) and prompt engineering in enterprise contexts
• Strong foundation in data architecture, data pipelines, and data governance practices
• Experience with DevOps and MLOps practices, including CI/CD, containerization (Docker), and orchestration (Kubernetes preferred)
• Proficiency in Python and the ability to guide engineering teams on implementation approaches
• Exceptional problem-solving and critical thinking skills, with the ability to navigate ambiguity and make informed trade-offs
• Relevant cloud or AI certifications (Azure, AWS, GCP) are a plus

• Lead the design of end-to-end AI/ML solutions, ensuring scalability, reliability, and alignment with client business objectives
• Translate ambiguous business challenges into clear, actionable AI strategies and solution architectures
• Define and guide implementation of enterprise AI systems, including data pipelines, model development workflows, and production inference architectures
• Architect scalable model-serving and distributed processing solutions that perform reliably in real-world environments
• Partner with client stakeholders to shape roadmaps, prioritize initiatives, and align technology decisions with business value
• Provide technical leadership across delivery teams, ensuring best practices in design, development, and deployment
• Evaluate and select appropriate tools, platforms, and frameworks to meet client needs across cloud ecosystems such as Microsoft Azure, Amazon Web Services, and Google Cloud
• Establish standards for performance, scalability, security, and governance across AI solutions
• Analyze system performance, model behavior, and data pipelines to identify optimization opportunities and improve outcomes
• Guide the responsible and ethical use of AI, including explainability, risk mitigation, and governance practices
• Mentor engineers and contribute to the growth and maturity of eimagine’s AI capabilities and delivery frameworks
• Stay at the forefront of emerging AI technologies and translate innovation into practical client recommendations