1460 Azure Application Development Architect jobs in New York,NY

New, Posted 1 day ago

Apply Directly

Service Desk Knowledge Architect

Curtiss-Wright

Parsippany, NJ 07054

RemotePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Information Technology or a related discipline
4+ years of experience in a similar role
Experience with managing operational priorities, mentoring staff, handling escalations, and performing administrative tasks simultaneously
Experience with training new hires with different levels of IT

SmartExplore AI is experimental.

Recommended

Easy Apply

Systems Architect

Hudson Technologies

Woodcliff Lake, NJ 07677

Remote

D365CE modules including Sales, Customer Service, Field Service, and Marketing
Dual Write (mandatory)
Dataverse and Power Platform
Strong understanding of integrations with D365 Finance & Operations
Excellent stakeholder communication and leadership skills
Familiarity with DevOps, CI/CD pipelines, and release management
Knowledge of data governance and security best practices
Strategic thinker with hands-on execution ability
Strong problem-solving and troubleshooting skills
Leadership in both project delivery and support environments
Ability to operate in fast-paced, evolving business environments
Bachelor's Degree in Computer Science or related field of study
10+ years of experience in Microsoft Dynamics ecosystem
Microsoft certifications in D365CE / Power Platform
Minimum 5 full-cycle D365CE implementations
Hands-on experience with customer journey orchestration and email marketing within D365
Proven experience leading support teams and post-go-live operations
Experience with Azure services, APIs, and middleware
Experience with Customer Insights and advanced segmentation/personalization strategies
Experience in industrial, manufacturing, or environmental services sectors
Not eligible for visa sponsorship

SmartExplore AI is experimental.

Recommended

Apply Directly

IT Infrastructure Architect, Staff

Curtiss-Wright

Parsippany, NJ 07054

RemotePaid Time OffRetirement Benefit

5-12 years of experience in infrastructure, systems engineering, or related roles
Broad experience in enterprise IT environments (not limited to a single system or tool)
Exposure to core infrastructure areas such as: Identity and access management (e.g., Active Directory or similar)
Server environments (Windows and/or Linux)
Application or platform support
Experience participating in system upgrades, migrations, or integrations
Demonstrated ability to learn and adapt to new technologies quickly
Strong communication and interpersonal skills
Proven ability to produce clear documentation with attention to detail
Exposure to Microsoft environments (Active Directory, Windows Server, SQL Server, Exchange) preferred
Experience with virtualization (e.g., VMware) preferred
Familiarity with cloud platforms (e.g., Azure) preferred
Exposure to CMDB or service management tools preferred
Experience working alongside ERP or business systems teams preferred
Any experience with platform ownership or application support preferred

SmartExplore AI is experimental.

Apply Directly

Outside Sales- Roofing and Siding Specialist

Riverhead Building Supply

Oceanside, NY 11572

OnsiteUrgently HiringRetirement Benefit

Bachelors degree or equivalent or 3-5 years of related work experience / training.
Excellent communication skills.
Working knowledge of database software.
Must demonstrate a positive, professional and courteous demeanor that represents the company professionally.
This position requires traveling to customers and job-sites.
Experience reading architectural plans for takeoffs preferred
Masonry and Hardscapes experience preferred

SmartExplore AI is experimental.

New, Posted 8 hours ago

Recommended

Apply Directly

Head of Technology, Intelligence Ventures

Spectrum

New York, NY 10036

OnsiteUrgently Hiring

Deep expertise across the full intelligence platform stack — including distributed data pipelines, ML platform architecture, embedding systems, feature stores, agent-to-agent API design, and LLM-powered application layers — with demonstrated ability to architect and ship all layers as a coherent, production-grade product
Demonstrated experience architecting and operating consumer data intelligence or data product platforms underpinned by complex machine learning systems and built on modern, cloud-native data infrastructure
Hands-on proficiency with Snowflake (including Cortex, Native Apps, and data sharing frameworks), cloud data platforms (AWS, Azure, or GCP), and production ML/AI systems at scale
Experience building agentic AI systems and LLM-powered product interfaces — including agent-to-agent APIs, retrieval-augmented generation architectures, and natural language UIs grounded in proprietary data — with strong product instincts around accuracy, trust, and user experience for non-technical enterprise audiences
Proven ability to translate complex technical architecture into clear executive and partner-facing communications; comfortable engaging at the C-suite level and in strategic partner negotiations with hyperscalers and technology platforms
Strong understanding of privacy-preserving data architecture, including differential privacy, de-identification techniques, zero-copy and clean room frameworks, and the regulatory landscape governing consumer behavioral data
Track record of recruiting and developing exceptional engineering talent in competitive markets; experience building high-performance teams from early-stage through scaled operations
Experience managing external development partners and outsourced engineering resources alongside an internal team in a fast-moving, build-from-scratch environment
Ability to operate in an ambiguous, early-stage environment while maintaining rigorous engineering standards and delivering against aggressive milestones
Experience building externally-consumed data or intelligence platforms — including developer-facing APIs, data marketplace integrations, or partner-accessible data products — with strong instincts around developer experience, access governance, and commercial platform design
Bachelor's Degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical field
Experience leading consumer data intelligence, AI/ML platform, or data product engineering organizations — 10 years
Engineering leadership and team-building experience, including managing senior technical staff — 7 years

SmartExplore AI is experimental.

Apply Directly

Manager, GCP Architect

KPMG

New York, NY 10025

Onsite

Minimum five years of recent Google Cloud Platform (GCP) or equivalent cloud systems development experience
Bachelor's degree from an accredited college/university
Applicants must be authorized to work in the U.S. without the need for employment based visa sponsorship now or in the future
Travel as required

SmartExplore AI is experimental.

Recommended

Apply Directly

Principal Quant Developer (MLOps)

Fidelity Investments

Weehawken, NJ 07086

~ 12 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field and six (6) years of experience as a Senior Quant Developer or similar role.
Alternatively, a Master's degree (or equivalent foreign education) in the same fields, accompanied by four (4) years of experience as a Lead Quantitative Development or similar role.
This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.
Expert in Python with experience across the development stack (full stack)
Exposure to object-oriented programming (OOP) and design patterns
Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability
Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
Proven ability to construct and manage robust data pipelines and event-driven workflows
Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2
Experience in containerization with Docker and orchestration with Kubernetes
Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management
Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning)
Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models
Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics
Awareness of responsible AI governance practices
Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset
Demonstrated knowledge of mathematics, statistics, and quantitative finance
Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
Domain knowledge in either equities, fixed income or alternative asset classes
Progress towards CFA (or equivalent) a plus

SmartExplore AI is experimental.

New, Posted 4 hours ago

Recommended

ResumeLibrary

AML Compliance Model Developer – Associate

Santander Holdings USA

New York, NY 10012

Onsite

Bachelor's degree in computer science, Information Systems, Data Analytics, Finance, Mathematics, or related field
3–5 years of experience in AML Compliance Technology, AML model development, or a related field within banking or financial services
Strong programming and analytical experience using SAS for data analysis, reporting, model support, and testing
Good working knowledge of Python for data manipulation, scripting, automation, and analytical processing
Strong SQL skills with experience developing complex queries, joins, procedures, and handling large-scale datasets
Experience working with Jira for Agile project tracking, sprint management, and defect lifecycle management
Working knowledge of testing methodologies including functional testing, regression testing, SIT, and UAT
Understanding of AML regulations and compliance frameworks including BSA/AML, OFAC, KYC, and transaction monitoring concepts
Strong analytical, quantitative, and problem-solving skills
Ability to multitask, manage priorities, and work effectively in fast-paced environments
Strong communication, documentation, and stakeholder management skills
Applicants must be legally authorized to work in the United States on a full-time basis without requiring employer sponsorship to commence employment

SmartExplore AI is experimental.

New, Posted 1 day ago

Recommended

Apply Directly

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.

SmartExplore AI is experimental.

Apply Directly

Chief Systems Engineer

L3 Harris

Clifton, NJ 07011

~ 30 min OnsiteBilingual PreferredEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's Degree with a minimum of 12 years of prior related experience.
Graduate Degree with a minimum of 10 years of prior related experience.
In lieu of a degree, minimum of 16 years of prior related experience.
2 years of experience in Cameo and SysML v1
3 years experience with Agile development and using JIRA
Active Secret Security Clearance- Ability to obtain and maintain any additional clearances as required.

SmartExplore AI is experimental.