OverviewThe Senior AI Architect leads the design and implementation of cutting-edge AI platforms and data systems. This role combines strong hands-on engineering with strategic innovation to design, prototype, and deliver intelligent, data-driven solutions that power analytics, machine learning, and next-generation AI applications. This role collaborates closely with business and technology teams to turn ideas into working solutions, enabling faster insights, better decisions, and enterprise-wide innovation through data.
ResponsibilitiesAdvanced AI Solutions & Engineering - Hands-on design and development of GenAI, LLM-based, and agentic AI solutions.
- Architect and implement repeatable, enterprise AI patterns (e.g., RAG, agent orchestration, multimodal pipelines) with working reference implementations.
- Build reusable AI components, templates, and accelerators to enable consistent adoption across teams.
- Implement and optimize scalable, secure, and resilient AI pipelines, aligned with enterprise data and governance standards.
- Lead PoC-to-production transitions, ensuring operational readiness, observability, and cost controls
AWS-Centric AI Architecture - Design AI and GenAI solutions using AWS-native services, including (but not limited to) Amazon Bedrock, SageMaker, Lambda, ECS/EKS, S3, DynamoDB, Aurora, OpenSearch, IAM, KMS, VPC, CloudWatch
- Define cost, performance, and scalability guardrails for AI workloads on AWS.
- Ensure architecture follows Well-Architected Framework principles.
Innovation & Applied AI - Lead initiatives to explore, validate, and scale emerging AI technologies.
- Translate research and prototypes into production-ready capabilities.
- Collaborate across teams to embed AI-driven insights and automation into business processes.
- Evaluate and shape next-generation AI trends, including agentic systems and autonomous workflows.
Technology Leadership & Best Practices - Champion hands-on experimentation and rapid solution delivery while maintaining technical excellence.
- Define and promote engineering standards that balance agility, scalability, and governance.
- Collaborate with security, compliance, and governance partners to ensure responsible data and AI usage
- Mentor engineers and architects in modern data and AI development practices.
Collaboration & Knowledge Sharing - Act as a trusted advisor for business and technology leaders on data-driven innovation.
- Lead internal workshops and training sessions to accelerate AI adoption.
- Represent the organization in external forums, conferences, and publications focused on data and AI innovation.
QualificationsBachelor's Degree and 6 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms OR High School Diploma or GED and 10 years of experience in Enterprise data architecture, advanced data solutions, cloud platforms
Preferred Qualifications: - 10+ years of experience in enterprise data architecture or engineering with deep expertise in AI and cloud-native data platforms.
- Proven ability to design and scale large-language-model (LLM) and generative AI systems.
- Proficiency in Python, SQL, and modern data frameworks
- Design AI and GenAI solutions using AWS-native services, including (but not limited to):Amazon Bedrock, SageMaker, Lambda, ECS/EKS
- Experience with Snowflake Cortex AI, Snowflake Native AI capabilities
- Strong background in distributed systems, and cloud architecture (AWS)
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- Relevant AWS certifications in cloud architecture, AI/ML, generative AI, or related domains
- Experience with agentic AI design patterns, including tool-use orchestration, autonomous workflow agents, or AI copilots.
- Proficiency in API design, microservices, and containerization (Docker, Kubernetes).
- Demonstrated ability to rapidly prototype new AI concepts and transition successful PoCs into production-grade systems.
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