Lead AI/ML vision, roadmap, and strategy. Design, develop, and deploy AI solutions. Mentor high-performing teams.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Role: Sr. AI Architect
Location: Oaks, PA
Full Time Role
Need candidate who can work onsite from Day 1 (Hybrid)
(also we provide relocation if candidate is not local)
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
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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
- 15+ years of experience in data science, machine learning, or advanced analytics
- 5+ years in a Architecture 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
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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 GCP)
- Experience driving enterprise AI transformation or center-of-excellence models
- Prior ownership of AI compliance, audit, or regulatory reviews
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