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Temporal Software Engineer Jobs in Dallas, TX (NOW HIRING)

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

... temporal mapping. - Decompose mining workflows into structured task sequences, labeling actions ... Desired (Nice to Have): - Background in Mining Engineering, Robotics, Autonomous Vehicles, or ...

Distinguished Engineer, Policy Platform

Dallas, TX · On-site

$150K - $300K/yr

  • Retirement

Deliver High-Quality services and software for a variety of domains * Accountable for the quality ... Deep knowledge of ETL, SQL, bitemporal datamodeling,and temporal databases. * Strong understanding ...

Tomahawk Flight Test Engineer

Dallas, TX

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience with RF spectral and temporal effects for sensor and backgrounds, including clutter ... mechanical, software, and computer engineering. * Experience in RF/EO integration of hardware ...

Solution Architect

Dallas, TX

$62.25 - $82/hr

What experience should you have: * 10+ years of software engineering experience, with at least 4 ... Temporal or comparable). You can read the codebase, make changes when it matters, and produce ...

Solution Architect

Dallas, TX · On-site

$62.25 - $82/hr

What experience should you have: * 10+ years of software engineering experience, with at least 4 ... Temporal or comparable). You can read the codebase, make changes when it matters, and produce ...

Solution Architect

Dallas, TX

$62.25 - $82/hr

What experience should you have: * 10+ years of software engineering experience, with at least 4 ... Temporal or comparable). You can read the codebase, make changes when it matters, and produce ...

ASDS Strike Initiatives Flight Test Lead P3

Dallas, TX

$47 - $64/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience with RF spectral and temporal effects for sensor and backgrounds, including clutter ... engineering disciplines, such as electrical, electronics, mechanical, software, and computer ...

Showing results 41-51

Temporal Software Engineer information

See Dallas, TX salary details

$62.8K

$145.9K

$203.3K

How much do temporal software engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for temporal software engineer in Dallas, TX is $145,935.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,700.00 and $171,100.00 per year, depending on experience, location, and employer.

What is the difference between Temporal Software Engineer vs Cloud Software Engineer?

AspectTemporal Software EngineerCloud Software Engineer
Required CredentialsBachelor's in CS or related, experience with Temporal SDKsBachelor's in CS or related, cloud platform certifications (AWS, Azure)
Work EnvironmentDeveloping distributed, event-driven applications using TemporalDesigning and deploying cloud-based solutions across platforms
Industry UsageTech companies implementing workflow orchestrationBroad industry use, including SaaS, enterprise, and startups
Search & Comparison IntentFocus on Temporal-specific skills and workflowsBroader cloud infrastructure and deployment skills

In summary, a Temporal Software Engineer specializes in building and maintaining workflow orchestration using Temporal, while a Cloud Software Engineer works on deploying and managing cloud-based applications across various platforms. Both roles require strong programming skills, but their focus areas differ significantly.

What is a Temporal Software Engineer?

A Temporal Software Engineer is a developer who specializes in building, maintaining, and optimizing applications using the Temporal open-source workflow orchestration platform. Temporal enables engineers to manage complex, long-running, and distributed workflows in a reliable and scalable way. Temporal Software Engineers typically design workflows, implement fault-tolerant logic, and help teams automate business processes that require reliability and durability. Their expertise ensures that workflows can recover from failures, maintain state, and handle retries without losing data or process integrity.

What are some common challenges faced by Temporal Software Engineers when designing workflows, and how can they be addressed?

Temporal Software Engineers often encounter challenges such as managing complex workflow dependencies, handling failure recovery, and ensuring workflow scalability. These challenges can be addressed by leveraging Temporal’s robust retry mechanisms, designing idempotent activities, and breaking workflows into smaller, reusable components. Collaboration with DevOps and QA teams is also crucial to ensure workflows are resilient and thoroughly tested in distributed environments.

What are the key skills and qualifications needed to thrive as a Temporal Software Engineer, and why are they important?

To thrive as a Temporal Software Engineer, you need strong software engineering fundamentals, proficiency in distributed systems concepts, and experience with languages like Go, Java, or TypeScript. Familiarity with Temporal's workflow orchestration platform, cloud infrastructure tools, and CI/CD systems is typically expected. Excellent problem-solving, collaboration, and communication skills help in designing resilient workflows and working with cross-functional teams. These skills are crucial for building reliable, scalable solutions that leverage Temporal for complex business processes.

What job categories do people searching Temporal Software Engineer jobs in Dallas, TX look for?

The top searched job categories for Temporal Software Engineer jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Temporal Software Engineer jobs?

Cities near Dallas, TX with the most Temporal Software Engineer job openings:

Director of Applied AI & ML Engineering

Paradigm

Irving, TX • Remote

Full-time

Re-posted 2 days ago


Job description

Paradigm is a software company transforming the way that the residential construction & building product industries operate across the globe. We are looking for a Director, Applied AI & ML Engineering to be part of revolutionizing these industries.

The Director, Applied AI & ML Engineering will lead the strategy, architecture, and deployment of intelligent systems that transform how homes are designed, estimated, and built. This role will drive the integration of AI and machine learning across the residential construction lifecycle—from digital plan understanding and takeoffs to automated estimating, material optimization, and design personalization.

The ideal leader blends technical depth with strategic clarity—able to guide teams across computer vision, large language models, and agentic automation while ensuring reliable, scalable delivery within the construction domain.

What You Will Do:

  • Define and lead the Applied AI & ML strategy for residential construction, identifying and prioritizing use cases that enhance speed, accuracy, and efficiency.

  • Build and maintain a roadmap of agentic AI systems that automate key construction workflows—such as plan interpretation, quantity takeoffs, cost estimation, and material specification optimization, while enabling seamless integration with suppliers, ERP platforms, and technology providers.

  • Partner with Product, Engineering, and Operations leaders to embed AI capabilities into core platforms and customer-facing applications.

  • Lead the design of AI-powered and multi-agent systems that connect workflows across design, estimating, procurement, and field execution.

  • Architect retrieval-augmented generation (RAG) and computer vision pipelines that interpret plan sets, generate takeoffs, and surface contextual insights.

  • Combine LLMs, CV, and rule-based logic to deliver explainable and auditable systems tailored to construction professionals.

  • Ensure architectural scalability, performance, and observability in all deployed systems.

  • Oversee the end-to-end ML lifecycle—from experimentation and model development to deployment, monitoring, and iteration.

  • Implement best practices in MLOps, data management, and continuous delivery pipelines.

  • Deliver measurable improvements in model quality, reasoning accuracy, and cost efficiency through advanced evaluation methods, such as Evals, zero- and few-shot benchmarking, Chain-of-Thought, and LLM-as-a-judge techniques to guide continuous model refinement.

  • Build, mentor, and lead a cross-functional team of applied AI and ML engineers, partnering closely with product, design, and software engineering teams to deliver production-grade AI-powered systems.

  • Foster a culture of collaboration, experimentation, and responsible AI development.

  • Manage vendor relationships and technology partnerships across cloud and AI platforms.

  • Collaborate with design, estimating, and operations teams to identify automation opportunities and ensure successful adoption.

  • Translate complex AI concepts into clear direction for business and product stakeholders.

  • Represent the organization’s AI vision in external partnerships, technical forums, and industry collaborations.

What You Need to Succeed:

  • 12+ years of experience in applied AI, ML, and/or Software engineering, with at least 5 years in a leadership role.

  • Bachelor’s or advanced degree in Computer Science, Machine Learning, or a related field preferred.

  • Proven success designing and deploying AI-driven systems in production environments.

  • Expertise in LLMs, computer vision, multimodal models, and retrieval-augmented generation (RAG) architectures.

  • Strong foundation in modern software engineering—including APIs, microservices, CI/CD, and containerization.

  • Hands-on familiarity with ML platforms such as MLflow, Kubeflow, or SageMaker for model training and deployment.

  • Demonstrated ability to collaborate across engineering, product, and operations in a complex technical environment.

  • Excellent written and verbal communication skills for both technical and executive audiences.

  • Experience in residential construction technology, including estimating, takeoffs, or design automation is preferred.

  • Background in BIM/CAD integration, digital twin platforms, or 3D modeling workflows is preferred.

  • Familiarity with agent orchestration frameworks (Temporal, n8n, LangGraph) and enterprise API integration is preferred.

  • Understanding of AI governance, auditability, and human-in-the-loop validation frameworks is preferred.

  • Experience with Azure, AWS, or GCP cloud platforms for scalable AI deployment is preferred.

Ready to Join? Apply now! MyParadigm.com/careers/
#Paradigm