AI Solutions Architect

eimagine is a company recognized as a Best Places to Work since 2015, committed to delivering value and outcomes for clients. They are seeking an AI Solutions Architect to lead the design and delivery of scalable AI solutions, guiding clients through complex business challenges and ensuring alignment with business objectives. Responsibilities: 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 Qualifications: 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 Required Skills: AI, Machine learning, Advanced analytics, Consulting, Microsoft Azure, Amazon Web Services, Google Cloud, Scalable system design, Distributed processing, Production-grade AI architectures, PyTorch, TensorFlow, Large language models, OpenAI API, Azure OpenAI API, Gemini API, Generative AI, Retrieval-augmented generation, Prompt engineering, Data architecture, Data pipelines, Data governance, DevOps, MLOps, CI/CD, Containerization, Docker, Orchestration, Kubernetes, Python