937 Developer Client Lifecycle Management jobs in New York,NY

Bachelor's degree in Engineering, Packaging, Supply Chain, Quality, or a related technical field required; advanced degree preferred.
8–12 years of experience in supplier quality, packaging components, manufacturing, supply chain, or vendor management.
Experience working in regulated environments, including GMP and quality systems, with familiarity in packaging components, supplier investigations, and change management.
Previous people leadership or team leadership experience preferred, with the ability to influence across sites and functions.

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AI Engineer

Capital One

New York, NY 10001

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Principal Engineer - Python API Development

Fidelity Investments

Hoboken, NJ 07030

~ 16 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.

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Technology Test Engineer

LMI Consulting, LLC

New York, NY 10001

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Information Technology Professional (IT Support)

U.S. Navy

Secaucus, NJ 07094

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Associate, Corporate Actions

BMO Financial

Jersey City, NJ 07305

Hybrid~ 22 minEducation AssistanceHealth InsuranceRetirement Benefit

5+ years' experience in asset servicing, with a Minimum of 3 years' experience in a voluntary corporate actions' role.
Within a Top/Mid-tier broker dealer or Bank
Strong AI proficiency with a demonstrated eagerness to learn and apply innovative solutions to enhance and optimize processes.
Undergraduate degree with a solid mathematics component, or an equivalent depth of knowledge via experience/training
Strong time management and organizational skills
A collaborative approach to working with teams in other geographical locations, for the running of BAU work as well as ongoing project work
Project Management experience seeing implementations and integration of key systems.
Strong Understanding of voluntary election arbitrage
Strong working knowledge of Canadian BPS, CDS, DTC and Microsoft office applications such as Excel
Solid understanding of business unit's risk and regulatory requirements
Work effectively with high volume of corporate action events that have deadline constraints
The ability to spot gaps, therefore risk, in the process, with the corresponding ability to provide workable solutions'

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