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Remote Process Engineering Manager Jobs in Dallas, TX

USM

JB061923 - AI Engineering

Southlake, TX · On-site +1

Skills NO Management experi.. Visa Types Green Card, US Citiz.. Here is a SOW Project Team Needed ... Southlake, TX (Hybrid - 4 days a week and Fridays are remote) Visa Status: Citizens, GC or GC/EAD ...

USAA

Director, Business Process Ownership

Plano, TX · On-site +1

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... process engineering/optimization. * 3 years of direct team lead, supervisory or management ...

AECOM

Water Process Engineer

Dallas, TX · On-site +1

AECOM Technical Services, Inc. is seeking a Water Process Engineer in Dallas, TX. Job Details ... and engineering to program and construction management. AECOM is a Fortune 500 firm that had ...

Danaher

Senior Engineer, Process Validation

Dallas, TX · On-site +1

$100K - $130K/yr

This position reports to the Process Validation Manager and is part of the Technical Operations ... Bachelor or master degree in engineering and 5+ years of experience * Prior experience in leading ...

Danaher

Senior Engineer, Process Validation

Dallas, TX · On-site +1

$100K - $130K/yr

This position reports to the Process Validation Manager and is part of the Technical Operations ... Bachelor or master degree in engineering and 5+ years of experience * Prior experience in leading ...

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Remote Process Engineering Manager information

See Dallas, TX salary details

$20.8K

$121.1K

$188.4K

How much do remote process engineering manager jobs pay per year?

As of Sep 11, 2026, the average yearly pay for remote process engineering manager in Dallas, TX is $121,146.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,500.00 and $143,400.00 per year, depending on experience, location, and employer.

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Remote Process Engineering Manager jobs near you
Infographic showing various Remote Process Engineering Manager job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, 3% Contract, and 1% Nights. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $121,146 per year, or $58.2 per hour.

AI Engineering Manager_Machine Learning

Plano, TX • Remote

VeeRteq Solutions Inc.
See more jobs at VeeRteq Solutions Inc.external

Contractor

Posted 20 days ago

Job description

Role:  Sr AI Engineering Manager_Machine Learning

Experience: - Min 10+ Years

Location: - Remote USA

We are looking for a Senior AI Engineer to design, build, and deploy high-quality AI-powered features with end-to-end ownership from prototyping to production, ensuring reliable, scalable, and impactful AI solutions.

Responsibilities: -

End-to-End AI Feature Ownership

  • Design and implement AI-powered features (LLM workflows, copilots, and agent-based systems with tool use and multi-step reasoning)
  • Own the Full Lifecycle: prototyping → evaluation → production deployment → iteration
  • Ensure solutions are reliable, performant, and aligned with product needs

AI System Implementation

  • Build and optimize prompt pipelines for specific use cases
  • Build retrieval systems (embeddings, chunking, ranking)
  • Implement RAG-based workflows where needed
  • Iterate on outputs to improve quality, accuracy, and consistency
  • Design scalable and cost-efficient AI architectures for production workloads
  • Select and evaluate models (hosted vs open-source) based on use case constraints

Agent-Based Systems (AgentCore)

  • Design and build agentic workflows capable of multi-step reasoning and decision-making
  • Integrate agents with tools, APIs, and internal systems to perform real-world actions
  • Implement planning, execution, and reflection loops for complex tasks
  • Manage context, memory, and state across multi-step interactions
  • Balance deterministic workflows vs. agent autonomy for reliability and control

Experimentation & Evaluation

  • Run structured experiments to compare approaches (prompting, retrieval, models)
  • Define and track key metrics for AI performance (quality, latency, cost)
  • Debug and improve non-deterministic system behavior
  • Build and maintain evaluation datasets and benchmarks
  • Implement automated evaluation pipelines for continuous improvement

Collaboration & Contribution

  • Drive technical direction and influence AI adoption across teams
  • Partner with product managers and designers to scope AI features
  • Contribute to shared patterns and reusable components
  • Participate in code reviews and design discussions
  • Support and mentor mid-level engineers where needed

AI Reliability, Safety & Governance

  • Design guardrails to ensure safe and reliable AI behavior
  • Mitigate hallucinations, prompt injection, and model misuse
  • Ensure compliance with data privacy and enterprise requirements
  • Implement monitoring and observability for AI systems in production
  • Implement guardrails for agent actions (tool access control, execution boundaries)
  • Prevent failure cascades in multi-step agent

 Educational Qualifications: -

  • Engineering Degree – BE/ME/BTech/MTech/BSc/MSc.
  • Technical certification in multiple technologies is desirable.

 

Skills: -

Mandatory skills

Core AI Skills

  • Strong understanding of LLM capabilities and limitations
  • Experience with prompt engineering and structured output design
  • Hands-on experience with embeddings and vector search
  • Familiarity with RAG architectures and when to apply them
  • Experience designing agent-based architectures (AgentCore concepts)
  • Understanding of tool use, planning strategies, and memory mechanisms in LLM systems

Engineering Skills

  • Min 4+ years of related work experience
  • Solid backend/system design fundamentals
  • Experience building and deploying production-grade systems
  • Ability to debug complex issues, including probabilistic outputs
  • Comfort working with APIs, pipelines, and data flows

Product Thinking

  • Ability to translate user needs into effective AI solutions
  • Strong intuition for balancing quality, latency, and cost
  • Focus on delivering measurable product impact

Collaboration

  • Communicates clearly across engineering and product teams
  • Contributes to team knowledge and shared practices.

 

Good to have skills

  • Evaluate agent performance across multi-step tasks (task success rate, error propagation)
  • Debug and optimize agent decision-making and tool selection behavior
  VeeRteq Solutions is an Equal Opportunity Employer