697 Database Engineer Software Development jobs in Rutherford,NJ

3+ years of business-to-business quota-bearing sales or equivalent sales experience
High School diploma or equivalent
Ability to read, write, speak and understand English
Demonstrated networking, negotiation and closing skills
"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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ResumeLibrary

Head of Engineering for Wealth Management

MassMutual

New York, NY 10012

~ 25 min Onsite

15+ years of progressive technology leadership experience, including leadership of large-scale software engineering organizations.
Experience leading organizations of 75+ engineers across multiple disciplines and geographic locations.
Proven track record modernizing enterprise platforms through cloud-native architectures, microservices, APIs, and event-driven systems.
Deep experience delivering customer-facing platforms in wealth management, capital markets, banking, fintech, retirement, or financial services.
Demonstrated success partnering with executive stakeholders to align technology investments with business outcomes.
Experience managing large-scale digital transformation initiatives with measurable business impact.
Must have Series 99 or ability to obtain it within 6 months.

SmartExplore AI is experimental.

New, Posted 6 hours ago

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Senior Manager, Software Development Engineer in Test

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$171,600-$230,100/yr

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Weehawken, NJ 07086

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.