927 Mid Level Devops Engineer jobs in Garland,TX

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Controls Business Development Manager (Building Automation Systems)-Dallas, TX

Top Tempo Technical - Dallas, TX

Controls Business Development Manager (Building Automation Systems)-Dallas, TX

~ 27 min Onsite

New, Posted 4 hours ago

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Principal Engineer - Python API Development

Fidelity Investments

Irving, TX 75061

~ 34 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 12 hours ago

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AI Engineer

Capital One

Plano, TX 75023

New, Posted 4 hours ago

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Principal Engineer - Python API Development

Fidelity Investments

Lewisville, TX 75029

~ 38 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 19 hours ago

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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.

New, Posted 6 hours 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 11 hours ago

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QA Analyst

BNS International

Mckinney, TX 75070

$126,131/yr

~ 30 min Onsite

Master's degree in Computer Science/Information Technology/ Business/Science/Engineering(Any) or closely related field with Six (6) months of experience in the job offered or as an IT Consultant or Analyst or Programmer or Developer or very closely related area.
Employer also accepts Bachelor's degree in Computer Science/Information Technology/Business/Science/Engineering (Any) or closely related field plus five years of progressive work experience in related field.
Experience Should include 6 (Six) Months of Working with Software Quality Testing.
Travel and/or relocation to unanticipated client sites throughout USA is required.
Travel and/or relocation is required to unanticipated client sites within USA.

SmartExplore AI is experimental.

New, Posted 19 hours ago

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Information Technology Professional (IT Support)

U.S. Navy

Rowlett, TX 75089

New, Posted 23 hours ago

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Actuarial Analyst I (Mid-Level)

USAA

Plano, TX 75023

RemoteUrgently HiringHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree; OR 4 years of related Actuarial/business/analytical experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
4 years of Actuarial or analytical business experience.
No more than 2 Casualty Actuarial Society (CAS) exams away from Associate of the Casualty Actuarial Society (ACAS) Credential and All Validation of Education Experience (VEEs) completed.
Demonstrated competency with relevant actuarial, mathematical, and statistical techniques and approaches used to support fact-based decision-making.
Intermediate knowledge of data analysis tools, data visualization, developing analysis queries and procedures in Python, R, SQL, SAS, BI tools or other analysis software, and relevant industry data & methods and ability to connect external insights to business problems.
Experience communicating complex solutions and analysis to both technical and nontechnical audiences.

SmartExplore AI is experimental.

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