Applied AI Solutions Architect
New
J
JobgetherArtificial Intelligence
Based in United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years of experience designing, building, or delivering Data, Analytics, Cloud, Software, Machine Learning, or AI solutions; 5+ years of experience designing or leading production AI, machine learning, MLOps, or data-intensive solutions.
- Required Skills
- PythonSQLArtificial IntelligenceCloud ComputingMachine LearningLLMMLOpsGenerative AI
Requirements
- 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.
Responsibilities
- 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.
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