AI Delivery Lead Full-Stack & SaaS Engineering

Overview ICE Mortgage Technology is digitizing and automating the entire real estate and housing finance lifecycle so critical data can flow seamlessly from one process to the next creating a better experience for the homeowner, lender and servicer. We are providing configurable technology, extensive data and comprehensive analytics that span the entire loan life cycle. Job Purpose The Development Manager - AI Agent & Full Stack Development will be responsible for managing the end-to-end delivery of AI-powered agent systems and intelligent automation solutions that enhance our mortgage servicing capabilities. This role combines hands‑on technical leadership with operational excellence, overseeing release management, environment operations, team delivery, and cross‑functional coordination to ensure our next‑generation intelligent applications are built, deployed, and maintained at production scale across multi‑tenant SaaS environments. Responsibilities Manages day‑to‑day delivery of AI agent and full stack development initiatives, ensuring on‑time, high‑quality releases aligned with business objectives and quarterly roadmap commitments Owns and drives operational excellence including release management, environment provisioning and maintenance (on‑premises and AWS), observability and alerting setup, and incident triage across development, staging, and production environments Coordinates with Operations teams on environment setups, infrastructure changes, deployment activities, and production support escalations Manages ServiceNow (SNOW) ticketing workflows for incident management, change requests, and service requests, ensuring SLA adherence and timely resolution Administers and maintains Azure DevOps (ADO) for project management including Features, Stories, Tasks, sprint planning, backlog grooming, and release tracking Provides technical leadership and people management to a team of software engineers, ensuring professional growth, skill development, and alignment with organizational goals Keeps up to date with trends in AI as it relates to solving business problems and guides the team in adopting best practices for AI/ML development and deployment Partners with Product Management, Architecture, QA, and DevOps teams to translate business requirements into actionable engineering plans with clear milestones and deliverables Designs and oversees the development of APIs necessary to affect front end functionality and/or be consumed by other partners Ensures full stack design and development quality across projects involving application development, migrations, and additions to existing applications Oversees front end application development utilizing React, Angular, Node.js, etc. in close accord with a UX team and ensures the responsiveness of those applications Oversees development of code libraries and APIs using Python and Java (Spring Boot) Manages delivery of AI solutions using AWS Bedrock and related services Enforces secure development practices which encompass secure coding, testing, access control, and secure deployment to build robust and resilient applications, with particular emphasis on protecting Non‑Public Information (NPI) and Personally Identifiable Information (PII) Ensures compliance with data privacy regulations and security standards applicable to financial services and mortgage industry (e.g., GLBA, SOC 2, PCI‑DSS) Oversees the design and creation of data models for applications and databases Facilitates software design meetings and analyzes user needs to determine technical requirements Reviews technical specifications based on conceptual design and stated business requirements Ensures development and execution of test protocols with an emphasis on automated Unit Tests, Component Tests, and Scenario Tests Manages documentation and procedures for installation, maintenance, and operational runbooks Mentors and guides software development staff, conducting regular code reviews, 1:1s, and performance assessments Manages capacity planning, resource allocation, and hiring activities to support team growth and delivery commitments Establishes and tracks engineering KPIs including velocity, quality metrics, deployment frequency, mean time to recovery (MTTR), and AI‑specific metrics such as LLM token usage, agent response times, and tool call success rates Remains current on industry standards in web development and AI/ML operations Performs additional related duties as assigned Knowledge and Experience A Bachelor's or Master's degree in Computer Engineering, Computer Science, or other related discipline; or equivalent combination of education and experience 10+ years of experience in Software Development with 3+ years in a people management or team lead capacity Demonstrated experience managing engineering teams in a SaaS provider environment delivering multi‑tenant applications at scale Prior experience working in industries that handle Non‑Public Information (NPI) and Personally Identifiable Information (PII) such as Financial Services, Mortgage, Banking, Insurance, or Healthcare Proven track record of delivering AI/ML applications to production including predictive AI, Generative AI, or Agentic AI solutions Experience managing operational responsibilities including release management, environment operations (on‑premises and cloud), observability/alerting, and incident management Experience with ServiceNow (SNOW) for ticketing, change management, and incident workflows Experience with Azure DevOps (ADO) for project management including Features, Stories, sprint management, and release tracking Experience working with development technologies including Python, .NET or Java/Spring, JavaScript Experience with OAuth2, JWT, JWS, JWE, JWKS/certificates, signing and encryption Experience with Open API Specifications 3.0 (OAS or Swagger) Experience working with OpenShift container platform and developing microservices Experience with API documentation tools and formats, such as Swagger and Postman, to create API documentation that is comprehensive, accurate, and up to date Experience with modern front‑end technologies such as React or Angular a plus Experience with RESTful services and SOAP Web services development Experience working with applications in the cloud such as AWS or Azure a plus Experience with Continuous Integration and Continuous Delivery (CI/CD) pipelines Experience with source code management tools such as Azure DevOps, TFS, Jira or Git Experience interacting with relational databases, such as MySQL, PostgreSQL, Oracle, or SQL Server Proficiency with development techniques such as Test‑Driven Development, Unit Tests, Component Tests and/or Scenario Tests a plus Familiarity working in a Software Development Life Cycle (SDLC) leveraging Agile principles and AI Tools such as GitHub Copilot, Claude Code or Cursor Experience working with software security platforms such as Snyk, and remediating security vulnerabilities Excellent analytical, decision‑making and problem‑solving skills Must be able to multitask in a fast‑paced environment with focus on timeliness, documentation, and communications with peers and business users alike Ability to communicate well both verbally and in writing to technical and non‑technical audiences of various levels within ICE or outside the organization (executives, regulators, clients, etc.) AI/ML & Agents 3+ years of experience managing or directly contributing to teams delivering AI/ML solutions to production environments Strong understanding of agent systems built using modern LLM frameworks (Ex: LangChain, LangGraph, Semantic Kernel) and foundation models from AWS Bedrock, OpenAI, or Azure OpenAI platforms Familiarity with Model Context Protocol (MCP) for server/client integrations, prompt engineering, and function/tool calling workflows in production environments Understanding of RAG patterns, vector database implementations, semantic search optimization, and autonomous agent architecture design Experience managing delivery of multi‑agent systems with awareness of patterns for orchestration, coordination, and memory management (short‑term and long‑term) Ability to evaluate, test, and monitor AI agent performance using established frameworks and methodologies for non‑deterministic systems Understanding of LLM security best practices including prompt injection prevention, data leakage mitigation, and responsible AI governance Operational & Delivery Management Demonstrated experience managing release cycles for enterprise SaaS applications including coordination of on‑premises and cloud (AWS) deployments Experience establishing and managing observability and alerting frameworks using tools such as Datadog, CloudWatch, Grafana, New Relic, or similar Proven ability to manage environment operations across multiple tiers (development, QA, staging, production) in both on‑premises and cloud infrastructure Experience with incident management processes including triage, root cause analysis, post‑mortem documentation, and corrective action tracking Track record of managing cross‑functional coordination with Operations, Infrastructure, Security, and Client Services teams Experience managing teams through regulatory and compliance‑driven release processes typical of financial services environments #LI-MA1 Intercontinental Exchange, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to legally protected characteristics. #J-18808-Ljbffr