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:
Bachelor's or Master's 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 .