Manager, Development

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

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