СШАApplied AI Architect - R01572122
2 нед. назад
150k–250k USD / годСШАRemote
etldata architecturecloud platformsaimachine learningprivacysecurity
Design and architect scalable, secure, and enterprise-ready AI systems solutions.
О компании
- is one of the fastest-growing digital technology service providers, helping Fortune 1000 organizations turn disruption into competitive advantage through innovative digital adoption.
- Our professionals combine deep technology expertise, design thinking, and a strong commitment to client success to deliver transformative outcomes.
- is recognized year after year as a Great Place to Work® , giving talented technology professionals the opportunity to work with cutting-edge technologies and solve complex, high-impact business challenges.
Обязанности
- As an Applied AI Architect, you'll own the technical foundations that make enterprise AI possible.
- You'll bring together data architecture, AI/ML systems, cloud platforms, enterprise integration, security, privacy, and governance to design solutions that can move beyond experimentation and into production.
- Design target architectures and scalable data pipelines for enterprise AI systems
- Architect ETL/ELT, feature stores, vector databases, knowledge layers, and AI data pipelines
- Evaluate and select AI models based on use case, performance, cost, latency, security, and governance requirements
- Design AI solutions that integrate with enterprise platforms including EHRs, core banking systems, CRM platforms, data lakes, and data warehouses
- Define and implement AI governance, compliance, privacy, and responsible AI frameworks
- Translate regulatory requirements into concrete technical and architectural controls
- Embed security, privacy, IAM, and data residency requirements from day one
- Design production environments across platforms such as Azure AI Foundry, AWS Bedrock, and Google Vertex AI
- Partner closely with AI Builders and Value Engineers throughout the lifecycle — from discovery through production
- Establish the foundations for MLOps, CI/CD, model lifecycle management, observability, monitoring, and evaluation
- Help move AI solutions from proof-of-concept into secure, scalable production environments
Требования
- Strong experience as an AI, ML, Data, Solutions, or Enterprise Architect, with hands-on experience designing and deploying AI solutions.
- Strong understanding of Generative AI, Agentic AI, RAG, AI orchestration, and modern AI architectures.
- Experience designing enterprise data architectures, pipelines, integrations, and scalable AI platforms.
- Experience evaluating AI models and understanding the tradeoffs between commercial and open-source models, as well as RAG versus fine-tuning.
- Experience with platforms and frameworks such as Azure AI Foundry, AWS Bedrock, Google Vertex AI, LangGraph, and LangChain.
- Experience integrating AI with enterprise systems and APIs. Healthcare experience with FHIR/HL7, Epic, or Oracle is a plus, as is financial services experience with payment data and core banking platforms.
- Strong understanding of AI governance, model risk management, responsible AI, privacy, security, and regulatory compliance.
- Experience working within regulated environments, with exposure to requirements such as HIPAA, GxP/CSV, AML, Basel III, or SR 11-7 highly desirable.
- Experience with enterprise security concepts including PHI/PII governance, data residency, VPC deployment, IAM, access control, and model inference security.
- Experience with production AI engineering, including CI/CD, MLOps, model registries, monitoring, observability, and evaluation frameworks.
- Strong communication skills and the ability to translate complex technical, business, security, and regulatory requirements into clear architectural decisions.
- If you're an architect who understands both the possibilities of AI and the realities of enterprise technology, security, data, and regulation, this is an opportunity to have a major impact.
Другое
- is looking for an Applied AI Architect who can turn ambitious AI strategies into secure, scalable, enterprise-ready systems.
- You'll help determine how AI solutions should be designed, what models should power them, how enterprise data should flow through them, and how they can operate safely within highly regulated environments.