Applied AI solutions Architect
RemoteUnited States or India
Job Summary
Design practical Applied AI solutions aligned to customer objectives, spanning predictive machine learning, MLOps, generative AI, LLM applications, and agentic workflows. Translate business problems into solution designs, implementation plans, and measurable outcomes while evaluating technology choices across cloud platforms and data ecosystems. Lead technical workstreams from discovery through production support, collaborating with stakeholders to resolve complex challenges and guide delivery. Contribute hands-on to prototypes, proofs of concept, and production implementations, ensuring solutions meet reliability, security, and governance standards. Support sales with technical proposals and demonstrations, communicating architectural decisions clearly to both technical and non-technical audiences.
Required Qualifications
- 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 AI, machine learning, MLOps, or data-intensive solutions in production
- Experience translating business and technical requirements into architecture, solution designs, and implementation plans
- Strong understanding of Applied AI and modern machine learning systems, including predictive ML, MLOps, generative AI, LLM applications, RAG, or agentic architectures
- Hands-on experience with production AI/ML systems, including considerations for evaluation, observability, security, governance, and operational support
- Experience with modern cloud, data, and AI ecosystems, including technologies such as Snowflake, Databricks, AWS, Azure, Google Cloud, dbt, Anthropic, OpenAI, or other modern AI frameworks
- Experience with programming and software development, preferably Python, as well as strong working knowledge of SQL
- Ability to collaborate effectively with business stakeholders and highly technical engineering teams
- Strong written and verbal communication, presentation, facilitation, and problem-solving skills
- Experience working in a consulting, professional services, product, or client-facing delivery environment
- Demonstrated ability to take ownership, manage multiple priorities, and deliver high-quality work with appropriate guidance
- Willingness to travel as needed to support customers, workshops, and strategic engagements
Desired Qualifications
- Experience with agentic AI systems, including orchestration, tool use, planning, memory, multi-agent patterns, or protocols such as MCP
- Experience designing and deploying enterprise RAG systems, semantic retrieval, AI applications, or intelligent workflow automation
- Experience with cloud-native AI/ML services such as AWS Bedrock and SageMaker, Azure AI/ML, Google Vertex AI, or Snowflake Cortex
- Experience with model registries, feature stores, data and model lineage, model monitoring, drift detection, AI evaluations, prompt management, or AI gateways
- Experience building reusable accelerators, modular architectures, or solutions deployed across multiple clients
- Industry experience building AI or machine learning solutions in life sciences, retail, financial services, manufacturing, or other enterprise environments
- Experience presenting technical solutions to customers or contributing to proposals, RFIs, RFPs, workshops, or demonstrations
- Contributions to open-source projects, technical communities, blogs, podcasts, or other technical thought leadership
- Bachelor's or master's degree in computer science, engineering, data science, or a related technical field—or equivalent practical experience
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