1116 App Security Engineer Devsecops Dast jobs in New York,NY

A high school diploma with an interest in manufacturing.
A performance-driven, team-oriented and customer-focused attitude/demeanor.
Good written/verbal communication skills and an impressive work ethic.
Strong attention to detail.
A strong mechanical/technical aptitude or background with a willingness to learn.
Ability to follow both written and verbal instructions in English.
Must be able to work in a production environment, and regularly lift up to 25 pounds.
Must be reliable and on time.
COVID-19 Vaccination is strongly encouraged.
This is a manufacturing facility-based position in Rockland County. You must presently live in or have a reasonable daily commute to the Rockland County area.
You must pass initial and random drug testing.

SmartExplore AI is experimental.

New, Posted 5 hours ago

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Specialist Director, Managed Security Testing

KPMG

New York, NY 10261

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IT Professional

U.S. Navy

Hoboken, NJ 07030

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Remote Customer Service

Hire Standard Staffing

New York, NY

$120,000/yr

RemoteHealth Insurance

Must be a U.S. or Canadian citizen

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Technical Trainer

Oerlikon Surface Solutions

Westbury, NY 11590

$95,000-$130,000/yr

~ 40 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Very experienced in Thermal Spray Technology and/or Surface Technology
Solid skills in developing training offerings and management and/or execution of the same
Strong personality with very good communication skills
Exceptional customer and service orientation as well as technology savvy with high problem solving skills
Experienced in international and cross-cultural business environment
Integrative personality and good organizing skills
Open personality with positive and supportive mindset

SmartExplore AI is experimental.

New, Posted 2 hours ago

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GEN AI Developer

Experis

Jersey City, NJ 07302

$85-$115/hr

~ 22 min OnsiteHealth InsuranceRetirement Benefit

5+ years of experience in Data Engineering, Analytics, or Machine Learning/NLP focused roles.
Experience with process mining tools such as Celonis or UiPath Process Mining.
Proven experience with cloud-based data pipelines.
Strong understanding of SQL, Python, and data transformation tools.
Exposure to or hands-on work with Generative AI, LLMs (like Llama, Google Gemini, OpenAI), or vector databases (e.g., Pinecone, FAISS).

SmartExplore AI is experimental.

New, Posted 4 hours ago

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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.