Applied AI Solutions Architect

Accountabilities:
As an Applied AI Solutions Architect, you will be responsible for designing, guiding, and delivering production-ready AI solutions while partnering with clients and internal teams to ensure successful outcomes. Lead the architecture and design of end-to-end Applied AI solutions spanning predictive machine learning, MLOps, generative AI, LLM applications, agentic workflows, and intelligent automation. Translate complex business needs into technical architectures, solution designs, implementation plans, and measurable success criteria. Support prototypes, proofs of concept, and production deployments by providing hands-on technical guidance and ensuring high-quality delivery. Collaborate with clients, architects, engineers, and cross-functional teams through discovery sessions, architecture workshops, and roadmap discussions. Recommend appropriate AI, cloud, and data technologies while helping stakeholders navigate complex technical decisions. Ensure AI systems are built with strong standards around security, scalability, observability, governance, cost optimization, and ongoing performance monitoring. Guide the transition of AI initiatives from early experimentation into reliable enterprise solutions. Contribute to reusable frameworks, technical accelerators, demonstrations, proposals, and knowledge-sharing initiatives. Requirements: The ideal candidate is a technically strong, client-oriented AI professional with experience designing and delivering modern data and AI solutions in complex environments. 8+ years of experience designing, building, or delivering Data, Analytics, Cloud, Software, Machine Learning, or AI solutions. At least 5 years of experience designing or leading production AI, machine learning, MLOps, or data-intensive solutions. Strong understanding of applied AI concepts, including predictive ML, generative AI, LLM applications, retrieval-augmented generation (RAG), and agentic architectures. Hands-on experience developing and operating production AI/ML systems, including evaluation, monitoring, security, governance, and lifecycle management. Experience with modern cloud, data, and AI ecosystems such as Snowflake, Databricks, AWS, Azure, Google Cloud, dbt, Anthropic, OpenAI, or similar technologies. Strong programming skills, preferably with Python, along with solid SQL knowledge and experience with software development practices. Ability to translate business requirements into scalable technical architectures and actionable delivery plans. Experience collaborating with enterprise clients and leading technical discussions with both technical and non-technical stakeholders. Bachelor’s or master’s degree in computer science, engineering, data science, or a related technical field, or equivalent practical experience. Experience with agentic AI systems, orchestration frameworks, enterprise RAG solutions, AI workflow automation, or cloud-native AI services is highly valued. Familiarity with model monitoring, feature stores, model registries, AI evaluations, prompt management, AI gateways, and data/model lineage is preferred. Strong communication, problem-solving, collaboration, and stakeholder management skills. Benefits: Remote-first work environment with flexibility to collaborate across distributed global teams. Competitive compensation package with excellent employee benefits. 401(k) plan with company match. Dental and vision insurance coverage. Home office equipment stipend to support remote productivity. Annual learning and development stipend to support professional growth. Four weeks of paid time off plus 10 company holidays. Access to challenging AI and data transformation projects with leading organizations. Opportunities for mentorship, career development, and continuous learning. Collaborative culture focused on innovation, autonomy, transparency, and meaningful impact. Inclusive workplace committed to supporting diverse backgrounds, perspectives, and experiences.

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