01Key Responsibilities
Build Define prioritized AI use cases with clear business outcomes and measurable success metrics. Prototype GenAI solutions (workflow automation, RAG, MCP, agentic orchestration) and drive production-ready AI & ML solution designs and handoff. Assess & Evaluate Lead end-to-end readiness assessments (architecture/semantic layer, platform/tooling, governance/controls, operational integration). Build and run an AI evaluation harness (golden datasets, automated metrics for quality/groundedness, safety, latency, cost) with benchmarking, regression tests, and release gates. Data & Architecture Support technical, data, and integration requirements; guide scalable AI data architecture patterns Consult on semantic layer design, metadata strategy, and data integration/lineage standards. Stakeholder/Cross functional Management Coordinate cross-functional delivery across business, enterprise AI program, engineering, data, and platform teams; align dependencies and milestones. Drive agile governance and executive reporting (backlog/Jira-Kanban hygiene, status/risk management, roadmap and leadership updates). Required Skills & Knowledge: Bachelors or Masters degree in Computer Science, AI/Data Science, Engineering, Economics or such related fields with 6+ years of handson experience in delivering ML & AI solutions or 8+ years of relevant experience in lieu of a degree. Handson experience in delivering GenAI solutions involving workflow automations (Copilot/n8n/Zapier/Make), RAG, MCP, Agentic AI Orchestration (using Langchain/LangGraph/CrewAI/AutoGen/AWS Strands) Experience building and operationalizing agentic AI in AWS (AgentCore/Bedrock), Azure (OpenAI Service), or GCP (Vertex AI) including secure tool/data access, guardrails, and monitoring/evaluation. Experience using tools such as SQL, SAS/Python, Spark/Scala/Hive, with demonstrated ability to apply Machine Learning techniques and efficiently work with complex, large-scale datasets. Strong expertise in semantic layers, enterprise data architecture, and data engineering, with proven proficiency in tools and frameworks such as Apache Spark, Airflow, Kafka, dbt, and Scala. 3+ years of team and project management experience leading cross-functional teams and initiatives, partnering with business and technology stakeholders, and synthesizing outcomes into executive-ready insights and recommendations. Desired Skills & Knowledge: Experience in the US banking, financial services, and credit card industry. Proven ability to operate effectively in highly matrixed organizations, with strong familiarity with Agile delivery .
