3156 Aws Cloud Developer Engineer jobs in Dallas,TX

Apply Directly

Principal Engineer - Python API Development

Fidelity Investments

Irving, TX 75061

~ 22 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

Principal Engineer - Python API Development

Fidelity Investments

Coppell, TX 75019

~ 31 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

Principal Engineer, IT Software

American Airlines

Fort Worth, TX 76101

Apply Directly

AWS Cloud Infrastructure & DevOps Engineer with Security Clearance

Gridiron IT Solutions

Dallas, TX 75201

New, Posted 1 day ago

Apply Directly

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

Keurig Dr Pepper

Frisco, TX 75033

Hybrid~ 29 minEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in related field (e.g., Computer Engineering, Information Systems, etc.) or equivalent combination of education and work experience.
Typically, 8+ years of experience in business analysis, quality assurance, or a hybrid BQAtype role supporting enterprise platforms
5+ years of DSD industry and Tell sell experience preferred.
Demonstrated handson experience with digital commerce, ordering, or customerfacing platforms (eCommerce, eB2B, tell sales, portals, or sales ordering systems)
Experience working with Salesforce platforms, preferably Commerce Cloud, B2B Commerce, or integrated eB2B solutions
Proven ability to translate business requirements into clear, testable acceptance criteria
Strong communication skills with the ability to collaborate effectively with Product, Engineering, QA, and business stakeholders
Ability to identify gaps, risks, and edge cases early to protect solution quality and business outcomes
Should have strong analytical, critical thinking, process modeling and decision making skills
Native-level proficiency/fluent in English.
Experience validating end-to-end order-to-cash or order lifecycle flows across integrated systems
Experience working in DevOps and Agile technology environments. (preferred)
Collaborate and share lessons learned regarding performance and reliability issues with all stakeholders including developers, other SREs, operations teams, and project management teams.
Salesforce Commerce Cloud, OCM or related Salesforce certification preferred

SmartExplore AI is experimental.

Easy Apply

Domain Managing Architect - Cloud

Horace Mann

Plano, TX 75074

~ 27 min Onsite

15+ years of IT experience with 8+ years in architecture leadership roles
Proven experience leading cloud transformation and legacy modernization programs at enterprise scale
Brings broad cross-domain knowledge spanning enterprise and solution architecture, data platforms, integration, infrastructure, networking, and security to design scalable, secure, and resilient enterprise solutions.
Experience working within an Enterprise Architecture framework (e.g., TOGAF).
Fluency in modern architecture practices, including cloud-native, microservices, event-driven, and AI-enabled architectures.
Proven experience leading legacy modernization and enterprise cloud transformation initiatives across complex technology landscapes.
Ability to define and govern enterprise architecture standards, patterns, reference architectures, and technology roadmaps aligned with business strategy.
Expertise in creating architecture artifacts and diagrams (e.g., Visio, draw.io).
Collaborate with business leaders, IT leadership, and engineering organizations to translate strategic objectives into scalable technology solutions.
Experience in risk management and executive-level presentations.
Knowledge of FinOps and Cloud cost optimization strategies
Demonstrated ability to lead across organizational boundaries and drive consensus.

SmartExplore AI is experimental.

ResumeLibrary