2476 Ai Full Stack Engineering Manager jobs in Dallas,TX
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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.
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Principal Engineer - Python API Development
Fidelity Investments
Bedford, TX 76022
~ 32 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.
New, Posted 1 day ago
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Developer/Sr Developer, IT Applications
American Airlines
Fort Worth, TX 76101
Easy Apply
Warehouse Packer TCS
Adecco
Coppell, TX 75019
$16/hr
~ 31 min OnsiteHealth InsurancePaid Time OffRetirement Benefit
- At least 1 year of warehouse experience
- Lift up to 50 lbs
- Stand for up to 8 hours per shift
- RF scanner experience
- Willingness to work in a non–climate-controlled warehouse
- Flexibility to adjust to shift changes after conversion
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Sr. Software Development Engineer
Disability Solutions
Frisco, TX 75034
Flexible Schedule
UPS - Warehouse Worker/Package Handler $21+/hr
UPS
Dallas, TX 75243
$21/hr
No Experience
New, Posted 13 hours ago
Easy Apply
General Production Position
Special Products & Manu
Rockwall, TX 75032
~ 32 min Onsite
- X High School or GED
New, Posted 13 hours ago
Easy Apply
Apprentice Pest & Termite Technician – Paid Training & Company Vehicle
All-Safe Pest & Termite
Lewisville, TX 75057
$27/hr
~ 33 min Onsite
- Valid driver's license (5+ years)
- Good driving record
- Ability to pass a background check and drug screen
Easy Apply
Work From Home Benefits Advisor - Entry Level
Hire Standard Staffing
Dallas, TX
$120,000/yr
RemoteHealth Insurance
- Must be a U.S. or Canadian citizen
Frito-Lay - Warehouser/Material Handler $18-$26/hr
Frito Lay
Dallas, TX 75206
$18-$26/hr
No Experience
New, Posted 4 hours ago
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Quality Inspector (2nd Shift)
BrassCraft Manufacturing Company
Lancaster, TX 75134
$22-$28/hr
~ 26 min OnsiteUrgently HiringBilingual Preferred
- 2+ years of Quality and Manufacturing experience.
- High School Degree
- Knowledge of blueprint reading and understanding.
- Knowledge of precision measuring tool use, nondestructive testing techniques. (preferred).
- Ability to perform inspection of quality-related data on incoming material, parts, sub-assemblies, and products using the required inspection tools. (Micrometers, calipers, height gages, thread and plug gages).
- Have good decision-making skills with the ability to effectively determine the quality of product prior to releasing or accepting.
- Ability to understand Quality Assurance processes and documentation to meet company quality standards (knowledge of ISO 9001:2015 Standards preferred).
- Ability to transfer, share, and relay information and statuses across shifts.
- Have the technical experience and knowledge base to understand Quality Control Plans and NCR's.
- Can take initiative to drive development in the Quality Department, team personnel, and facility
- .read and understand drawings, SOP's, inspection reports, and AQL sampling plans.
What companies are hiring Ai Full Stack Engineering Manager jobs in Dallas,TX?
- Fidelity Investments
- American Airlines
- Adecco
- Disability Solutions
- UPS
- Special Products & Manu
- All-Safe Pest & Termite
- Hire Standard Staffing
- Frito Lay
- BrassCraft Manufacturing Company
- Fidelity Investments
- American Airlines
- Adecco
- Disability Solutions
- UPS
- Special Products & Manu
- All-Safe Pest & Termite
- Hire Standard Staffing
- Frito Lay
- BrassCraft Manufacturing Company
What is the hourly salary range for Ai Full Stack Engineering Manager jobs in Dallas,TX?
The hourly salary range is $16 - $28.
The hourly salary range is $16 - $28.
