1106 Aws Java Developer jobs in New York,NY

~ 12 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Principal Engineer - Python API Development

Fidelity Investments

Weehawken, NJ 07086

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.

iHire

AI Engineer

Capital One

New York, NY 10001

~ 18 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Principal Engineer - Python API Development

Fidelity Investments

Secaucus, NJ 07094

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.

iHire

Engineer

Capital One

New York, NY 10001

Technology Test Engineer

LMI Consulting, LLC

New York, NY 10001

IT Systems Administration JOB Training Program

Year Up United

New York, NY 10261

$525/wk

Onsite

A high school graduate or GED recipient
Eligible to work in the U. S.
Highly motivated to learn technical and professional skills
Have not obtained a Bachelor's degree
You may be required to answer additional screening questions when applying

Easy Apply

Remote Customer Service

Hire Standard Staffing

New York, NY

$120,000/yr

RemoteHealth Insurance

Must be a U.S. or Canadian citizen

Software Development JOB Training Program

Year Up United

New York, NY 10261

$525/wk

Onsite

A high school graduate or GED recipient
Eligible to work in the U. S.
Have not obtained a Bachelor's degree
You may be required to answer additional screening questions when applying

New, Posted 1 hour ago

Onsite Technology Testers Needed (NYC) - $150 Payout

uTest by Applause

New York, NY 10009

$25 bonus

89% of jobs ask for a resume

Don't let the perfect job slip away—upload your resume and we'll personalize your results instantly.

89% of jobs ask for a resume

Don't let the perfect job slip away—upload your resume and we'll personalize your results instantly.

New, Posted 18 hours ago

OnsiteHealth InsuranceRetirement Benefit

Senior Associate, ServiceNow Software Asset Management (SAM)

KPMG

New York, NY 10025

Minimum of three years of experience with techniques such as assessing and planning IT capabilities, IT cost and performance management, IT solutions architecture, portfolio, program and project management, and transformational change
Bachelor's degree in Computer Science, Computer Engineering or related technical field from an accredited college/university
Deep understanding and hands-on experience with ServiceNow Software Asset Management (SAM), in addition to broader ServiceNow, IT management, enterprise strategy, IT supply chain, and information management disciplines
Experience in IT process improvement within your own organization or as an external consultant
Strong business, technical, analytical, problem-solving, and verbal and written communication skills