IT Engineering Manager

Cantor Fitzgerald•Dallas, TX

10d•Hybrid

About The Position

Lead, grow, and retain multiple high-performing engineering teams spanning full-stack, data engineering, and AI/agentic AI builders. Own end-to-end delivery, quality, reliability, and operational health of cloud-native platforms across front-end, backend, data, and AI layers. Manage, mentor, and develop engineers and senior engineers; set clear goals, deliver performance reviews, and drive career growth. Own hiring end to end, building strong, diverse teams through effective recruiting, interviewing, onboarding, and workforce planning. Set and enforce engineering standards and best practices for architecture, code quality, testing, security, and deployment, including responsible use of AI-assisted development tools. Partner with product, design, data, and business leadership to translate strategy into scalable technical roadmaps and prioritized execution plans. Drive adoption of agentic AI, LLM tooling, and modern engineering practices to increase developer velocity and unlock new product capabilities. Provide architectural guidance and lead technical design reviews across full-stack, data engineering, and AI initiatives. Establish healthy Agile and delivery processes, metrics, and operational rigor, including planning, estimation, on-call, and incident management. Manage cross-team dependencies, risks, and coordination for complex, multi-quarter initiatives. Foster a culture of ownership, inclusion, technical excellence, and continuous learning. Communicate status, tradeoffs, and technical concepts clearly to both engineers and senior or executive stakeholders. Balance hands-on technical involvement with people leadership, remaining credible and close to the work while leading through others.

Requirements

Bachelor's degree in Computer Science, Engineering, MIS, or related field preferred.
12+ years of experience in software or data engineering, including 4+ years directly managing engineering teams.
Proven track record of building, scaling, and retaining high-performing engineering teams.
Broad technical breadth across full-stack web development (JavaScript/TypeScript, React; backend languages such as C#, Node.js, or Java), data engineering (SQL, Python, cloud data platforms, ETL/ELT), and AI (LLM and agentic AI, RAG).
Strong understanding of distributed systems, microservices, API design (REST/GraphQL), and cloud-native architecture (Azure, AWS, or GCP).
Experience delivering data platforms and pipelines, with familiarity with data modeling, governance, and/or master data management (MDM) concepts.
Hands-on familiarity building or integrating agentic AI and LLM-powered systems and orchestration frameworks (e.g., LangChain, AutoGen, Semantic Kernel, MCP).
Strong grasp of CI/CD, infrastructure as code, and DevOps/DataOps practices.
Excellent people leadership, communication, and stakeholder-management skills.
Proven ability to drive delivery across multiple teams and influence technical direction across the organization.

Nice To Haves

Experience managing managers or team leads within a multi-team organization.
Experience leading teams that have shipped AI/ML or agentic AI products to production at scale.
Experience with event-driven and streaming architectures and real-time data processing (e.g., Kafka, Event Hubs, Kinesis).
Familiarity with containerization and orchestration (Docker, Kubernetes) and workflow orchestration (Airflow, Dagster, dbt).
Prior experience in commercial real estate, fintech, or operations/transaction systems.
Track record of speaking, writing, or open-source and community leadership, especially in applied AI.

Responsibilities

Lead, grow, and retain multiple high-performing engineering teams spanning full-stack, data engineering, and AI/agentic AI builders.
Own end-to-end delivery, quality, reliability, and operational health of cloud-native platforms across front-end, backend, data, and AI layers.
Manage, mentor, and develop engineers and senior engineers; set clear goals, deliver performance reviews, and drive career growth.
Own hiring end to end, building strong, diverse teams through effective recruiting, interviewing, onboarding, and workforce planning.
Set and enforce engineering standards and best practices for architecture, code quality, testing, security, and deployment, including responsible use of AI-assisted development tools.
Partner with product, design, data, and business leadership to translate strategy into scalable technical roadmaps and prioritized execution plans.
Drive adoption of agentic AI, LLM tooling, and modern engineering practices to increase developer velocity and unlock new product capabilities.
Provide architectural guidance and lead technical design reviews across full-stack, data engineering, and AI initiatives.
Establish healthy Agile and delivery processes, metrics, and operational rigor, including planning, estimation, on-call, and incident management.
Manage cross-team dependencies, risks, and coordination for complex, multi-quarter initiatives.
Foster a culture of ownership, inclusion, technical excellence, and continuous learning.
Communicate status, tradeoffs, and technical concepts clearly to both engineers and senior or executive stakeholders.
Balance hands-on technical involvement with people leadership, remaining credible and close to the work while leading through others.