1434 Azure Aws Cloud Solution Architect jobs in Dallas,TX

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Principal Business Quality Analyst (BQA) -Salesforce Commerce Cloud eB2B

Keurig Dr Pepper - Frisco, TX

Principal Business Quality Analyst (BQA) -Salesforce Commerce Cloud eB2B

Hybrid~ 29 minEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

New, Posted 1 day ago

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Network Deployment Technician, GND-NASA-Deploy

Amazon Data Services

Wilmer, TX 75172

Requires TravelUrgently HiringHealth InsurancePaid Time OffRetirement Benefit

2+ years of computer networking experience
2+ years of Linux operating systems experience
Experience in computer networking
Experience with computer hardware troubleshooting and repair
Bachelor's degree in Information Technology, Computer Science, or a related field; or equivalent work experience in a relevant technical discipline.
Physical Requirements (all physical requirements may be done with reasonable accommodations). This position has a physical component requiring the ability to lift & rack equipment up to 40lbs; it may require working in cramped spaces or in elevated locations while adhering to health & safety guidelines.
This role may involve up to 50% travel; the vast majority is local travel but may have the potential to include domestic and international travel to support the organization.

SmartExplore AI is experimental.

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Irving, TX 75061

~ 22 min OnsiteUrgently HiringEducation 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.

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Developer/Sr Developer, IT Applications

American Airlines

Fort Worth, TX 76101

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IT Solution Architect: Human Capital & Talent Management

Coca-Cola Southwest Beverages

Dallas, TX 75240

Onsite

Minimum of 5 years of experience working with SAP HCM/SuccessFactors solutions, including integration and development experience across modules/systems:
SAP SuccessFactors – Employee Central
SAP SuccessFactors – Learning
SAP SuccessFactors – Performance Management/Goal Management
SAP SuccessFactors – Recruitment
SAP SuccessFactors – Compensation
SAP – HCM
3rd party tools for Learning and Recruiting (e.g., LinkedIn, Indeed, JJ Keller, Tech Systems, etc.)
Bachelor's degree or foreign equivalent in Computer Science, Engineering, or a related field.
Proven track record of high performance in supporting Human Capital Management & Talent Management IT solutions and business processes, with knowledge of HCM Planning & Execution KPIs.
Experience in process analysis & redesign, consulting & relationship management, and project management (including coordinating work delivery within a multi-team environment).

SmartExplore AI is experimental.

New, Posted 1 day ago

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Principal Engineer - Python API Development

Fidelity Investments

Southlake, TX 76092

~ 36 min OnsiteUrgently HiringEducation 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.

New, Posted 1 day ago

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IT Support Associate II, OTS

Amazon.com Services LLC

Richardson, TX 75080

Urgently Hiring

New, Posted 1 day ago

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Solution Architect

KPMG

Dallas, TX 75201

New, Posted 8 hours ago

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Salesforce Application Architect

Keurig Dr Pepper

Frisco, TX 75033

~ 29 min OnsiteUrgently HiringEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Master's or Bachelor's degree in related field (e.g., Computer Science, Computer Engineering, Electrical Engineering, Information Technology, System Analysis, etc.) or equivalent combination of education and work experience
10 – 12+ years of experience in IT and business/industry including strategic and operations planning
10+ years of experience in at least three disciplines, such as business, information, solution, or technical architecture, application development, middleware, information analysis, database management, or operations
Experience in working in multiple, diverse technologies and processing environments.
3–5 years of IT experience including Salesforce architecture, design, and delivery.
Knowledge of SDLC methodologies with experience delivering Salesforce solutions in Agile and DevOps environments
Proven ability to translate strategic vision into executable Salesforce roadmaps.
Ability to lead cross-functional teams and communicate effectively with business stakeholders.

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EPIC ODB Engineer / Architect - Remote

NTT DATA Americas

Plano, TX 75086

Remote

7–10+ years of experience supporting Epic as an ODBA, DBA, or database architect.
Epic certifications in Chronicles, ODBA, or related technical modules (e.g., Cache/IRIS).
7–10+ years ofDeep expertise with InterSystems Caché/IRIS, including globals, journaling, shadowing, and performance tuning.
7–10+ years of strong understanding of Epic architecture, including Hyperspace, Interconnect, Web Blob, and ancillary systems.
7–10+ years of Proficiency with Linux/UNIX administration and shell scripting.
7–10+ years of Experience with high‑availability architectures, clustering, SAN/NAS storage, and virtualization.
7–10+ years of Strong analytical and troubleshooting skills for complex, high‑volume clinical systems.

SmartExplore AI is experimental.