1043 Forward Deployed Ai Engineer Enterprise jobs in New York,NY

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Head of AI Data Science, Intelligence Ventures

Spectrum

New York, NY 10036

OnsiteUrgently Hiring

Deep expertise in transformer-based sequence modeling and its application to behavioral or interaction data at consumer scale — including architecture design, training methodology, fine-tuning, and embedding quality evaluation
Proven track record developing and deploying household- or user-level embedding models applied to real-world use cases in media, marketing, commerce, and/or customer intelligence — not just research environments. Demonstrated understanding of the unique characteristics of behavioral sequence data: sparsity, temporal dynamics, multi-entity structure, and the signal differences between behavioral intent and explicit interaction
Strong command of the full data science lifecycle in production settings — from exploratory data analysis and feature engineering through model training, validation, deployment, monitoring, and iteration — at large dataset scale (billions, even trillions of records)
Hands-on proficiency with Python, PyTorch or TensorFlow, and distributed ML training frameworks; experience running ML workloads on cloud platforms (AWS SageMaker, Snowflake Cortex, Databricks, or equivalent)
Experience designing and operationalizing feature stores and predictive modeling pipelines that serve downstream intelligence products, audiences, or decision systems in production environments
Ability to communicate complex AI/ML concepts clearly to non-technical executive audiences, product stakeholders, and external partners; comfort operating as an external-facing technical spokesperson for the platform's modeling capabilities and intelligence differentiation
Track record of leading and growing high-performing data science teams; experience recruiting and developing senior ML talent in competitive markets
Genuine intellectual curiosity about the application of AI to behavioral science, consumer intelligence, and agentic systems; awareness of the evolving landscape of foundation models, retrieval-augmented generation, and multi-agent AI architectures
Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative field
Experience leading applied ML or data science teams building consumer-facing or enterprise intelligence products — 7 years
Hands-on experience designing and training transformer or deep learning models on sequential behavioral data at scale — 5 years
In-office position preferably based in New York City
Travel as required for partner engagements, executive meetings, and industry events

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Enterprise Business Development Manager (BDM)

Aiola

New York, NY 10060

Paid Relocation to New York, NY

Remote

5+ years in enterprise B2B business development or sales, with a proven track record of cold outbound into US-based Fortune 500 / Enterprise accounts. Your concrete wins include outbound-originated pipeline, not only inbound conversion.
Business acumen. You can hold a credible, peer-level business conversation with a VP of Field Sales, Regional Sales Leaders, or RevOps — you understand how their organization runs and what keeps them up at night, and you lead with that, not a feature pitch.
Prospecting craft. You know how to break into named accounts and multi-thread a buying committee. You're tool-agnostic and comfortable executing on a lean stack — we run HubSpot and Apollo on day one, not a heavy enterprise tooling suite.
Complex-cycle expertise. Deep understanding of long, multi-stakeholder enterprise sales cycles.
Executive presence. You engage C-suite and VP-level stakeholders with credibility, curiosity, and high business acumen.
Entrepreneurial grit. You thrive in a fast-moving startup, take ownership, and solve for ambiguity — and you're expected to produce qualified pipeline inside your first 90 days, not after a quarter of stack-building.

SmartExplore AI is experimental.

New, Posted 14 hours ago

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Enterprise Account Manager, NYC

Spectrum

New York, NY 10010

Urgently Hiring

Two or more years of B2B sales experience as a proven sales performer
High school diploma or equivalent
Knowledge of computer networking, internet solutions and fiber connected networks
Relationship-building, negotiation, closing and English communication skills
Quick learner with the ability to manage change and shifting priorities
Travel to and from assigned territories and company facilities
Valid driver's license
**This role requires the ability to work lawfully in the U.S. without employment-based immigration sponsorship, now or in the future.**

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Senior Distinguished Engineer, AI Compute (Remote Eligible)

Capital One

New York, NY 10001

Remote

New, Posted 1 day ago

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Software Engineering/Applications Leadership Advisory - Executive Technology Services for Global Enterprises

Gartner

Newark, NJ 07175

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Systems Analyst – Enterprise Automation

MassMutual

New York, NY 10012

Onsite

Bachelor's degree in Computer science, engineering or other applicable discipline
8+ years of experience in business analysis, process improvement, automation, or digital transformation roles.
5+ years of experience working with Robotic Process Automation (RPA) platforms (e.g., UiPath or similar)

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AI Engineer

Capital One

New York, NY 10001

New, Posted 1 day ago

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Senior Enterprise Sales Account Executive

Lightpath

White Plains, NY 10606

$75,000-$175,000/yr

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Weehawken, NJ 07086

~ 12 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.