AI Architect for Automation Delivery - BFS (Remote)

Key Responsibilities

• AI-Led Automation Architecture
• End-to-end architecture of AI/ML/GenAI/Agentic AI solutions—including model selection, data pipelines, orchestration layers, integration patterns, and deployment architecture—tailored for BFS use cases such as KYC/AML, fraud detection, credit decisioning, servicing, and regulatory reporting
• Define reference architectures, reusable frameworks, and engineering standards for automation and AI workloads across financial operations
• Architect solutions using cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex), IPA platforms (UiPath, Power Platform), and custom Python-based pipelines, ensuring compatibility with core banking systems, payment platforms, and risk engines
• Conduct technical feasibility assessments, including data availability, model readiness, integration constraints, and infrastructure requirements within regulated BFS environments
• Own the technical delivery lifecycle: requirements, solution design, development oversight, testing, deployment, and hypercare
• Guide engineering teams on model training, prompt engineering, RAG pipelines, vector databases, orchestration frameworks, and automation workflows supporting high-volume financial processes
• Implement CI/CD pipelines, MLOps practices, and automation deployment frameworks aligned with BFS governance and auditability needs
• Drive performance tuning, model evaluation, monitoring, and continuous improvement of deployed AI systems
• Establish AI governance and AI strategy including model lifecycle management, versioning, auditability, and risk controls consistent with BFS regulatory expectations
• Lead AI programs, driving alignment between business stakeholders, technical teams, and delivery partners, with experience navigating BFS risk, compliance, and operational constraints

Required Skills & Qualifications

• Strong practitioner experience designing and implementing AI/ML pipelines, GenAI solutions, RAG architectures, and agent-based systems
• Hands-on experience with cloud AI platforms: Azure AI / Azure OpenAI, AWS AI/ML stack, GCP Vertex AI
• Experience with vector databases (Pinecone, FAISS, Chroma, Redis), embeddings, prompt engineering, and LLM orchestration frameworks
• Proficiency in Python, API development, microservices, and automation frameworks
• Strong understanding of scalable architecture and clean coding practices
• Experience delivering AI or automation solutions within regulated financial institutions
• Strong understanding of workflow orchestration, event-driven architectures, and enterprise integration patterns
• Experience integrating AI with core systems (policy admin, claims, CRM, data lakes, APIs), including BFS platforms such as core banking, payments, lending, and risk systems
• Proven ability to lead large-scale AI automation delivery programs with complex technical dependencies
• Strong background in MLOps, DevOps, CI/CD, model monitoring, and production deployment
• Experience conducting architecture reviews, threat modeling, and performance optimization
• Ability to create technical roadmaps, solution blueprints, and engineering playbooks