Job Description We are seeking an experienced Senior AI Solutions Architect to lead the design, deployment, and advisory of enterprise AI solutions for banking and financial services clients. The successful candidate will have strong expertise in Agentic AI, Site Reliability Engineering (SRE), cloud platforms, cybersecurity, and enterprise architecture, with the ability to engage senior stakeholders and deliver innovative, secure, and scalable AI solutions. Key Responsibilities Agentic AI & AI Platform Engineering Design, develop, and deploy multi-agent AI systems for banking and financial services use cases. Build AI evaluation frameworks to ensure model quality, explainability, governance, and compliance. Manage the end-to-end AI deployment lifecycle from solution design through production implementation and post-deployment support. Ensure AI platforms meet enterprise standards for reliability, observability, security, and auditability. Site Reliability Engineering (SRE) Implement SRE best practices, including defining Service Level Objectives (SLOs), Service Level Agreements (SLAs), and error budgets. Design monitoring and observability solutions using logs, metrics, and distributed tracing. Lead incident management, root cause analysis, and continuous service improvement. Manage release management, change management, disaster recovery, and business continuity planning. Cybersecurity & Data Protection Design enterprise cybersecurity architectures including Data Loss Prevention (DLP), endpoint security, and identity & access management. Integrate AI-powered security monitoring and threat detection capabilities. Implement security controls aligned with regulatory requirements and industry best practices. Collaborate with security teams to strengthen governance, risk management, and compliance. Client Advisory & Solution Delivery Conduct discovery workshops with senior client stakeholders to understand business and technology requirements. Lead Proof-of-Concept (PoC) engagements and deliver measurable business outcomes. Present technical solutions and business value to executive leadership and decision-makers. Support business development by providing technical expertise during client engagements and industry events. Requirements Degree in Computer Science, Information Technology, Computer Engineering, Software Engineering, or a related discipline. Extensive experience in enterprise AI solution architecture and production AI deployment. Strong knowledge of Agentic AI, LLM applications, AI orchestration, and AI operations (AIOps). Experience in Site Reliability Engineering (SRE), cloud infrastructure, observability, and production operations. Strong understanding of cybersecurity principles, including DLP, IAM, SIEM, endpoint security, and cloud security. Knowledge of financial services technology environments and regulatory compliance is highly preferred. Excellent stakeholder management, communication, and presentation skills. Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform. Preferred Certifications AWS, Microsoft Azure, or Google Cloud Professional Certifications ISC2 Certified Cloud Security Professional (CCSP) or CISSP CISM or equivalent cybersecurity certification ACAMS or relevant financial compliance certification AI/ML Operations or Generative AI certifications