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
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
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
