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5270 Director Ai Engineering jobs in New York,NY

New, Posted 4 hours ago

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Principal Software Engineer

Mastercard

Harrison, NY 10528

RemoteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Extensive experience in designing and delivering large-scale, distributed systems and platforms.
Proven ability to influence technical strategy and drive architectural decisions across multiple teams.
Strong expertise in modern software engineering practices, cloud-native architectures, and AI/data platforms.
Exceptional communication and leadership skills with a track record of mentoring and thought leadership.
Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline.
Data Architecture & Strategy
Focus on designing modern, scalable, governed data ecosystems.
Data strategy and product-aligned data architectures
Modern database technologies and migration away from legacy Oracle
Data lakehouse architectures supporting analytics and ML workloads
Feature catalog / feature engineering platforms
High-Throughput, Low-Latency, and Real-Time Systems
Critical for Mastercard's real-time decisioning and event-driven platforms.
Event streaming and high-throughput data pipelines
Low-latency data technologies (distributed caches, grid replacement)
Real-time transaction processing and sub-second decisioning
Rules engine design and modernization
Cloud Infrastructure, Platform Engineering & DevOps
Driving cloud-native engineering practices and operational excellence.
AWS infrastructure engineering and cloud-native platform patterns
DevOps and platform engineering (automation, CI/CD, observability, GitOps)
ML lifecycle engineering (model training, deployment, refresh, inference)
Deep, progressive experience in software engineering.
Proven technical leadership roles influencing architecture and design across multiple teams.
Proven track record of delivering large-scale, distributed systems and enterprise-grade platforms.

SmartExplore AI is experimental.

New, Posted 1 day ago

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Director, Applied AI Product Manager

BNY

New York, NY 10261

$127,000-$260,000/yr

New, Posted 22 hours ago

Senior Staff Engineer, Interactive Voice Response - AI/ML

Geico - Government Employees Insurance Company

New York, NY 10025

New, Posted 6 hours ago

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Solution Director of Data & AI

TATA Consultancy Services

New York, NY 10261

$171,000-$190,000/yr

New, Posted 6 hours ago

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Senior Engineering Director (Remote)

Jobgether

New York, NY 10261

RemoteFlexible Schedule

New, Posted 5 hours ago

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Engineering Manager

Tremendous

New York, NY 10261

$5,000/mo

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Founding AI Engineer

RDE Advisors

New York, NY 10261

New, Posted 5 hours ago

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AI Model Engineer - Remote/Nationwide

Signature Performance

New York, NY 10261

$100,000-$140,000/yr

Remote

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Head of AlphaGen - Investor Research Product Engineering, Director

Blackrock

New York, NY 10007

HybridEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent practical experience.
Strategic Engineering Leadership: Proven experience leading large-scale engineering organizations through product transformation initiatives (e.g., platform modernization, cloud migration, operating model changes).
Demonstrated success in setting vision and executing across complex, multi-year technology programs.
Demonstrated strength in partnership-building and cross-functional collaboration.
Able to influence and align product teams, platform/infrastructure teams, and governance bodies around a common vision and roadmap.
Ability to operate in complex market and organizational contexts, translating strategic objectives into actionable plans.
Proven track record of driving innovation, navigating ambiguity, and delivering measurable outcomes at scale.
AI-First, Human-in-the-Loop: Embraces AI-driven solutions as a default for efficiency and scale, while keeping expert human judgment in critical loops to ensure quality and trust.
Platform Over People: Prioritizes building robust platforms and automation over relying on individual heroic efforts, enabling sustainable and scalable growth.
Single Front Door: Advocates for a unified user experience where researchers and stakeholders have one intuitive portal for all their needs, simplifying access and support.
Standardization Everywhere: Drives consistency in tools, processes, and data across the board, reducing complexity and improving interoperability and maintainability.
Self-Service as the Default: Champions self-service capabilities, empowering users to accomplish tasks independently (from data ingestion to model deployment) without bespoke engineering work.
Deep Co-Ownership with PMG: Fosters a culture of partnership with the Portfolio Management Group, aligning closely on priorities, sharing roadmaps and KPIs, and co-owning outcomes to ensure the platform truly meets investment teams' needs.
Alpha generation workflows or closely related quantitative research processes in finance/investments.
Cloud technologies and cloud-native architectural patterns (e.g., microservices, containerization, distributed computing e.g. Ray).
API-first platform design and developer experience best practices.
AI/ML applications for workflow automation, data validation, and operational excellence
Modern stack knowledge and skills - e.g. Python, Polars, Ray, MLFlow or equivalent technology