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Engineering Manager Transformer Jobs in Laredo, TX

The Enterprise Architect will play a critical role in transforming local, legacy, datadriven ... Define and maintain technical standards for enterprise data management, analytics platforms, and AI ...

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Engineering Manager Transformer information

See Laredo, TX salary details

$40.8K

$128.9K

$152.7K

How much do engineering manager transformer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for engineering manager transformer in Laredo, TX is $128,921.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,300.00 and $151,900.00 per year, depending on experience, location, and employer.

What is an engineering manager transformer?

An Engineering Manager Transformer is a leadership position focused on managing teams that develop, implement, and maintain transformer models, which are a type of machine learning model commonly used in natural language processing and other AI applications. This role combines technical expertise in transformer architectures with management responsibilities such as team coordination, project oversight, and mentoring engineers. Engineering Manager Transformers play a crucial role in setting technical direction, ensuring best practices, and facilitating collaboration across cross-functional teams. Their work impacts the successful deployment of large-scale AI solutions and helps organizations stay at the forefront of machine learning innovation.

What are the key skills and qualifications needed to thrive as an engineering manager transformer?

To excel as an Engineering Manager Transformer, you need a deep understanding of electrical engineering principles, transformer design, and manufacturing processes, usually backed by a bachelor’s or master’s degree in electrical engineering. Familiarity with CAD software, power system analysis tools, and industry standards such as IEEE or IEC, along with relevant certifications like Professional Engineer (PE), is highly valuable. Strong leadership, problem-solving abilities, and effective communication distinguish top performers in this role. These competencies are crucial for ensuring technical excellence, team productivity, and the successful delivery of complex transformer projects.

What are some typical challenges an engineering manager transformer faces when leading cross-functional teams?

Engineering Manager Transformers often navigate complex project requirements that require close collaboration between electrical, mechanical, and software engineering teams. One common challenge is aligning diverse technical perspectives and ensuring effective communication to meet project deadlines. Additionally, balancing resource allocation while maintaining high standards for safety and compliance can be demanding. Successful managers foster a collaborative environment and proactively address any knowledge gaps within the team to deliver high-quality transformer solutions.

What is the difference between Engineering Manager Transformer vs Data Engineer?

AspectEngineering Manager TransformerData Engineer
Required CredentialsBachelor's/Master's in Engineering, Computer Science; leadership experienceBachelor's in Computer Science, Data Science, or related field; technical skills in data systems
Work EnvironmentLeading teams, project management, cross-department collaborationBuilding and maintaining data pipelines, data modeling, database management
Employer & Industry UsageTech companies, AI/ML firms, organizations deploying Transformer modelsData-driven companies, analytics firms, AI/ML organizations

While both roles involve technical expertise, the Engineering Manager Transformer focuses on leading teams developing Transformer-based AI models, whereas Data Engineers build and maintain the data infrastructure supporting such models. The former emphasizes leadership and project management, while the latter concentrates on data pipeline development.

What cities near Laredo, TX are hiring for Engineering Manager Transformer jobs?

Cities near Laredo, TX with the most Engineering Manager Transformer job openings:

Sr. Solution Architect

Munich Re

Laredo, TX • On-site

Full-time

Medical, Life, Retirement, PTO

Re-posted yesterday


Job description

Role Overview

We are seeking a Data and AI Enterprise Architect with deep expertise in Data, Analytics, and Artificial Intelligence (AI) to join the IT Enterprise Architecture organization. This role is accountable for proactively leading data, analytics, and AIdriven technology transformation initiatives and enabling measurable business outcomes across the enterprise.

The Enterprise Architect will play a critical role in transforming local, legacy, datadriven processes, and systems into centralized, scalable, and groupwide platforms, while ensuring alignment with enterprise architecture standards and business strategy.

Enterprise Architects provide technical leadership across analysis, design, facilitation, and execution, supporting the evolution of enterprise Data, Analytics, and AI capabilities and the associated application portfolios and technology stacks. The role owns the creation of key architectural deliverables such as targetstate architectures, transformation roadmaps, standards, and guidelines to enable successful project delivery and longterm strategic outcomes.

This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework, with a strong emphasis on cloudbased data platforms, AI enablement, and data governance.

The ideal candidate will help advance organizational directives around simplification, modernization, and innovation by providing architectural leadership in enterprise data platforms, integration components, and AIenabled data strategies.

Key Responsibilities

  • Assist in the development of a multiyear Data, Analytics, and AI roadmap, aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with Data & Analytics Enterprise Architects.
  • Drive standardization of Data, Analytics, and AI technology standards, principles, and guidelines across multiple business entities.
  • Define and maintain technical standards for enterprise data management, analytics platforms, and AI enablement capabilities.
  • Design and guide datacentric and AIenabled initiatives, supporting the transition from traditional data architectures to nextgeneration cloud, analytics, and AI platforms.
  • Act as an evangelist and ambassador for enterprise architecture standards including Data Governance. Data Intake and Ingestion. Data Modeling, Data Integration, Analytics and AI lifecycle management
  • Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives and implementations.
  • Identify technologyrelated business pain points by mapping business capabilities to current platforms, leveraging EA practices and participating in innovation activities, including AI adoption.
  • Enable IT development and infrastructure teams to make informed technology decisions through frameworks, reference architectures, standards, and reusable patterns.
  • Identify technical risks, architectural gaps, and vulnerabilities that could impact project delivery or lead to postrelease defects.
  • Reduce cost and complexity through standardization, reuse, and rationalization of data, analytics, and AI platforms.
  • Partner with EA and TA peers (enterprise, solution, and business architects) to derive the futurestate technology architecture, aligned to business strategy and external trends.
  • Define migration and transformation plans to close gaps between current and target states, in alignment with Business Solutions and Business Technology Architects.
  • Support governance, assurance, and compliance activities to ensure alignment with enterprise architecture standards and policies.
  • Assess and articulate the organizational, skills, process, and financial impact of changes to the application portfolio, data platforms, and AI stack.
  • Define and govern enterprise AI architecture standards, including model lifecycle management, MLOps, and AI platform integration.
  • Ensure responsible and compliant AI adoption, aligned with AI governance, model risk management, data privacy, and security controls.
  • Guide the integration of AI/ML capabilities into analytics platforms, including predictive, prescriptive, and generative AI use cases.
  • Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions.
  • Establish architectural patterns for AI model deployment, monitoring, versioning, and retraining in cloud environments.
  • Evaluate emerging AI technologies, tools, and platforms and provide strategic recommendations for enterprise adoption.

 

Your Profile

  • 4+ years of experience in Enterprise Architecture or Technical Architecture.
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or Business (or equivalent).
  • Strong experience with cloud platforms and services, including:
    • Azure (e.g.; Azure AI Studio, Azure Data Services and tools)
    • AWS  (e.g.; Amazon Bedrock, Sagemaker, Data Services and tools)
    • Databricks
  • Handson experience with enterprise data concepts, including:
    • Data Intake and Ingestion
    • Data Warehousing
    • Data Lakes / Lakehouse architectures
    • ETL / ELT
    • Interactive and operational reporting
    • Statistical and regulatory reporting
    • Master Data Management (MDM)
    • Data Governance, Quality, Security, Audit, Balance & Control
  • Solid understanding of enterprise architecture practices, including:
    • Architectural patterns
    • Roadmaps
    • Architecture Review Boards
    • Solution Design Boards
  • Experience defining data management and AI roadmaps, cloudbased services, and reusable architectural patterns.
  • Experience integrating operational data with enterprise data lakes.
  • Strong understanding of data integration challenges and solution patterns.
  • Experience with statistical and data science languages such as Python and R (strong asset).
  • Exposure to AI/ML concepts, including model development, deployment, monitoring, and MLOps (required).
  • Familiarity with Generative AI concepts, AI platforms, and enterprise adoption considerations (strong asset).
  • Strong business acumen with deep understanding of:
    • Financial systems
    • Corporate and backoffice systems
    • Enterprise data management, analytics, and AI technology landscape
  • Strong problemsolving skills, unquestioned integrity, and high collaboration capability.
  • Passion for innovation, continuous improvement, modernization, and change management.
  • Excellent written and verbal communication skills, with the ability to communicate effectively at all levels.
  • High sense of ownership, accountability, and pride in delivered outcomes.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company's Princeton location.

The base salary range anticipated for this position is $141,800 - $207,900 plus opportunity for company bonus based upon a percentage of eligible pay.  In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO). 

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range.