Description:
Client: Point32Health Plan
Location: Boston, MA (Remote)
Position Summary
The AI Architect is responsible for defining the enterprise AI strategy, designing scalable AI and Generative AI solutions, and leading the technical architecture for AI-driven products and business transformation initiatives. The role bridges business objectives with emerging AI technologies, ensuring secure, scalable, ethical, and compliant AI implementations across cloud and on-premises environments.
The AI Architect works closely with business stakeholders, enterprise architects, data engineers, security teams, application developers, and data scientists to deliver production-ready AI solutions while establishing enterprise AI governance, standards, and best practices.
Key Responsibilities
AI Strategy & Architecture
Define enterprise AI architecture aligned with business strategy and digital transformation objectives.
Design scalable AI, Machine Learning (ML), and Generative AI solution architectures.
Develop AI reference architectures, reusable frameworks, and implementation standards.
Evaluate emerging AI technologies and recommend adoption strategies.
Establish enterprise AI roadmaps and technology blueprints.
Solution Design
Design end-to-end AI solutions integrating enterprise applications, cloud platforms, APIs, and data platforms.
Architect Retrieval-Augmented Generation (RAG), AI agents, copilots, intelligent automation, and conversational AI solutions.
Define model selection strategies for LLMs, foundation models, and traditional ML models.
Design vector databases, prompt engineering frameworks, embeddings, and orchestration pipelines.
AI Platform & Engineering
Design AI platforms leveraging Azure AI, AWS AI, Google Vertex AI, OpenAI, Anthropic, or similar technologies.
Define scalable MLOps and LLMOps architectures.
Establish model lifecycle management, CI/CD pipelines, monitoring, and version control.
Optimize AI infrastructure for performance, scalability, reliability, and cost efficiency.
Governance, Risk & Compliance
Establish AI governance frameworks, responsible AI principles, and model risk management practices.
Ensure compliance with AI regulations, privacy requirements, and security standards.
Define controls for data protection, explainability, bias detection, model monitoring, and auditability.
Collaborate with GRC, Privacy, and Security teams to implement AI risk controls.
Security Architecture
Design secure AI solutions following Zero Trust principles.
Define security controls for AI models, APIs, prompts, embeddings, and training data.
Implement identity management, encryption, access controls, and secure deployment practices.
Address AI-specific threats including prompt injection, model poisoning, data leakage, and adversarial attacks.
Technical Leadership
Provide architectural guidance to AI engineers, data scientists, and development teams.
Lead architecture reviews and technology assessments.
Mentor technical teams on AI best practices and emerging technologies.
Drive innovation through proof-of-concepts (POCs), pilots, and accelerator development.
Stakeholder Management
Collaborate with Enterprise Architects, CISO, business leaders to identify AI opportunities.
Translate business requirements into AI solution architectures.
Present architecture designs and technical recommendations to executive stakeholders.
Support pre-sales activities, solution proposals, and client workshops.
Required Qualifications
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
Master's degree preferred.
10+ years of experience in software engineering, cloud architecture, or enterprise solution architecture.
5+ years of experience designing enterprise AI or Machine Learning solutions.
Required Technical Skills
Artificial Intelligence
Machine Learning
Deep Learning
Generative AI
Large Language Models (LLMs)
Natural Language Processing (NLP)
Computer Vision
Reinforcement Learning (preferred)
GenAI Technologies
OpenAI
Azure OpenAI
Anthropic Claude
Google Gemini
Meta Llama
Mistral
Hugging Face
AI Frameworks
LangChain
LangGraph
LlamaIndex
Semantic Kernel
CrewAI
AutoGen
Programming
Python
Java
C#
REST APIs
SQL
JavaScript (preferred)
Cloud Platforms
Microsoft Azure AI
AWS AI Services
Google Cloud Vertex AI
Data Technologies
Azure Data Platform
Databricks
Snowflake
Vector Databases (Pinecone, Weaviate, Milvus, Azure AI Search)
SQL/NoSQL databases
MLOps / LLMOps
MLflow
Azure ML
Kubeflow
Docker
Kubernetes
GitHub Actions
Azure DevOps
Security & Governance
AI Governance Frameworks
Responsible AI
Model Monitoring
Data Privacy
AI Risk Management
AI Security
India DPDP Act
Soft Skills
Strategic thinking and innovation
Strong analytical and problem-solving abilities
Executive-level communication and presentation skills
Leadership and mentoring capabilities
Stakeholder management
Cross-functional collaboration
Ability to simplify complex technical concepts for business audiences
Preferred Certifications
Microsoft Certified: Azure AI Engineer Associate
Microsoft Certified: Azure Solutions Architect Expert
AWS Certified Machine Learning Engineer
Google Professional Machine Learning Engineer
Databricks Certified Machine Learning Professional
NVIDIA AI Certifications
TOGAF
Certified Information Systems Security Professional (CISSP) (preferred)
ISO/IEC 42001 Lead Implementer or Lead Auditor (preferred)
Key Deliverables
Enterprise AI Strategy and Roadmap
AI Reference Architecture
AI Solution Designs
GenAI and Agentic AI Architecture
AI Governance Framework
AI Security Architecture
MLOps/LLMOps Framework
Architecture Review Reports
Technology Evaluation and Recommendation Documents
AI Standards and Best Practices
Proof of Concepts (POCs) and Technical Accelerators