AI Architect

Role: AI Architect

Location: Oaks, PA

Mode Of Hire: Full Time

Key Responsibilities

• Define and own the enterprise AI/ML vision, roadmap, and long-term strategy aligned with business goals
• Lead design, development, deployment, and lifecycle management of AI and machine learning solutions
• Build and mentor high-performing AI, data science, and ML engineering teams
• Partner with Product and Business leaders to identify high-impact AI use cases and prioritize initiatives
• Establish best practices for model development, validation, monitoring, explainability, and retraining
• Ensure AI solutions comply with data privacy, security, regulatory, and ethical AI guidelines
• Oversee AI platform architecture, model pipelines, and MLOps frameworks for scalability and reliability
• Drive adoption of generative AI, predictive analytics, NLP, and advanced modeling techniques where applicable
• Communicate AI strategy, performance, and risks clearly to executive leadership and stakeholders
• Evaluate and manage AI vendors, tools, platforms, and cloud services

Required Qualifications

• Experience with Financial services, Wealth management is preferred to have.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
• 10+ years of experience in data science, machine learning, or advanced analytics
• 5+ years in a leadership or people-management role overseeing AI/ML teams
• Strong hands-on experience with ML models, statistical methods, and AI frameworks
• Experience deploying AI solutions in production environments at scale
• Hands on RAG experience: embeddings, retrieval strategies, chunking, metadata/routing, evals, and guardrails.
• Open source frameworks: strong with LangChain (or similar), plus experience with FastAPI/Flask and async patterns.
• Azure: practical experience with Azure OpenAI/Models, Azure AI Search, Azure ML, AKS/Container Apps, Key Vault, App Insights/Log Analytics, and Hybrid Private Networking.
• Terraform: modules, CI/CD integration, and handling nested data structures.
• MLOps/DevOps: Docker/Kubernetes, CI/CD (Gitlab or Azure DevOps), secrets management, and automated testing.
• Solid understanding of LLMs (prompting, function/tool calling, structured outputs, rate limiting, token/cost management).
• Proficiency with Python, SQL, and modern data/ML platforms (cloud-based preferred)
• Strong understanding of data governance, model risk management, and responsible AI practices
• Excellent communication skills with the ability to translate complex AI concepts for non-technical audiences

Preferred / Nice-to-Have

• Experience in financial services, healthcare, life sciences, or other regulated industries
• Exposure to generative AI, large language models (LLMs), and prompt engineering
• Familiarity with MLOps tools, CI/CD for ML, and cloud platforms (AWS, Azure, or Google Cloud Platform)
• Experience driving enterprise AI transformation or center-of-excellence models
• Prior ownership of AI compliance, audit, or regulatory reviews