We're seeking an AI Solution Architect to drive the design and implementation of enterprise-scale artificial intelligence solutions. This role combines deep technical expertise in AI/ML with strategic architectural vision, focusing on integrating generative AI models with Salesforce, AWS, Databricks, and critical business systems. The ideal candidate will architect scalable ML infrastructure using AWS SageMaker and Databricks, while implementing cutting-edge LLM solutions and autonomous AI frameworks. You'll be responsible for establishing robust MLOps practices, ensuring cost optimization, and maintaining compliance with AI regulations. This position requires expertise in modern AI technologies, including prompt engineering, LangChain, and Salesforce Agentforce, along with a strong foundation in enterprise architecture and technical leadership.
Responsibilities/accountabilities will also include:
- Design and implement enterprise AI solutions integrating with enterprise platforms
- Build ML infrastructure on AWS SageMaker and Databricks platforms
- Design autonomous AI systems using LangChain, LlamaIndex, and AutoGPT
- Architect and deploy enterprise Agents with Agentforce, N8N, AgentCore solutions with custom Integrations
- Create and enforce organizational AI technical solution blueprints
- Design cross-environment authentication frameworks
- Manage AI infrastructure costs and regulatory compliance
- Establish model governance and compliance frameworks
- Implement comprehensive CI/CD pipelines for AI
- Lead architecture reviews and technical decisions
Qualifications and required experience
- Master's/PhD in Computer Science (AI/ML specialization), Data Science, or related field (or Bachelor's with relevant industry experience)
- Massive work experience in enterprise software development, solution engineering, or AI/ML consulting
- Relevant production experience with Large Language Models and generative AI and hands-on experience with AWS SageMaker and/or hands-on experience with Databricks
- Extensive experience with MLOps platforms including SageMaker Pipelines, Model Registry, and Feature Store implementation at enterprise scale
- Deep expertise in foundation model development, fine-tuning, and deployment using AWS Bedrock and related technologies
- Advanced knowledge of data engineering practices including Delta Lake, Spark optimization, and enterprise-grade streaming architecture
- Expert-level Salesforce architecture experience, including multi-org deployment strategies, data model optimization, complex integration patterns, and enterprise security implementation including Shield Platform Encryption and AI security protocols
- Deep expertise in Generative AI and LLM systems, including advanced prompt engineering, RAG architecture with multi-stage retrieval, vector database optimization, and comprehensive LLM security testing and safety implementations
- Proven track record in strategic AI leadership, including translating technical concepts for C-level stakeholders, leading cross-functional teams (5-15 engineers, data scientists, architects) and developing comprehensive business cases with ROI analysis