AI Engineer Jobs in Dallas, TX
AI Engineer jobs in Dallas, Texas are concentrated in Uptown, the Platinum Corridor along the North Dallas Tollway, and Deep Ellum, with strong demand across financial services, healthcare technology, and enterprise software. Employers hiring right now include Amazon Web Services, Deloitte, and Goldman Sachs. See the openings below and apply to the ones that match your experience.
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Job Description
Overview
The Data & AI Project Analyst serves as the field-facing connector between project teams, account leadership, owners/JV partners, and DPR’s Technology & Innovation groups—translating business needs into scalable data, analytics, integration, and AI solutions. This role engages early to shape requirements, standardize approaches across projects, coordinate delivery with U.S. and offsite teams, and ensure all data sharing and AI use aligns with governance, legal, and contractual obligations. This is a jobsite-based role, which will require regular travel between all jobsites within a national account.
Data & Development
- Engage early in pursuit and preconstruction to:
- Identify owner-mandated technologies
- Capture data requirements and reporting obligations
- Surface integration needs and constraints
- AI opportunity identification
- Partner with:
- Integration Managers
- Account Leadership
- Project Teams to align on scalable and repeatable approaches
- Other Account leads
- Other T&I Groups - (CT, IT, ETS)
- Align project-level data needs with DPR’s Data Strategy and enterprise standards, delivering consistent, flexible solutions that drive measurable impact across the account.
- Translate business and project needs into clear data, analytics, and integration requirements.
- This role is primarily field-based, with approximately 75% of time spent on active jobsites and limited opportunity for remote work. This includes participation in key meetings and workgroup meetings at the jobsite.
- Align AI use cases with owner expectations and contract constraints
- Advise on feasibility and value of AI-driven solutions
Data & Integration Enablement
- Influence strategic technology decisions related to data, analytics, AI, and development.
- Lead conversations with owners, JV partners, and stakeholders on data exchange approaches, including:
- System access vs data sharing
- File-based vs platform-based integrations
- Reporting vs operational use cases
- Guiding the team through custom analytics and development.
- Responsible for coordination with Data Engineering, Solution Architecture, Analytics and offsite teams to:
- Define integration approaches
- Ensure feasibility and scalability, avoiding one-off or unsustainable solutions
- Act as a Funnel for requests with US and Offsite teams
- Manage UAT and QA/QC for deliverables, collaborating with U.S. and offsite teams to incorporate feedback, and own final production readiness and quality.
- Drive data readiness and integration strategies to support scalable pipelines and enable effective consumption of predictive and generative AI models.
- Support implementation of standardized data exchange frameworks and templates
- Ensure all external data sharing aligns with data governance, legal, and contractual requirements
- Provide hands-on support in analytics and Power BI, iterating on reports, making minor updates, and developing proof-of-concept solutions based on real-time user feedback.
Intake, Prioritization & Coordination
- Act as the front door for data and development requests at the account level
- Work with Data & Development Lead – Mega Projects for the prioritization across the accounts
- Ensure requests are:
- Clearly defined
- Properly scoped
- Prioritized based on business impact
- Coordinate execution across:
- Data Engineering
- Data Analytics
- AI/ML
- Software Development
- Add AI-specific intake criteria (value, risk, data readiness)
- Prioritize AI initiatives alongside analytics and development work
- Coordinate across AI/ML teams for model development and deployment
- Track progress, manage expectations, and communicate updates to stakeholders
- Escalate risks, conflicts, and capacity constraints when needed
Standardization & Reuse
- Identify opportunities to:
- Reuse existing dashboards, pipelines, and integrations
- Avoid duplication across projects and accounts
- Promote standardized approaches for:
- Data mapping
- Integration patterns
- Reporting structures
- Drive implementation of AI use cases by prioritizing reusable models, prompts, and workflows, and minimizing one-off, non-scalable solutions.
- Contribute to the development of templates and best practices for mega projects.
Project Onboarding & Enablement
- Support setup of new projects by:
- Aligning on data requirements and integrations
- Facilitating access to systems and tools
- Coordinating onboarding workflows (data, analytics, reporting)
- Work with Integration Managers to understand account-level and project-level technology stacks including:
- DPR standard tools
- Owner-mandated systems
- JV partner systems
- AI/ML tools, platforms, and model usage
- Track approved vs non-approved AI technologies
- Identify implications of introducing AI into project tech stacks
- Partner with Integration Managers to deliver and support project landing pages, access management workflows, standardized setup processes, and effective analytics storytelling for project teams.
- Facilitate rollout of dashboards and tools, including training and enablement for internal and external project teams for onboarding, access, and effective data usage.
- Champion the use of existing tools and platforms across project teams to drive consistency and maximize value.
- Assess the technology stack and identify deviations from standards, evaluating downstream impacts on data, development, AI, integrations, cost, and support.
Data Governance & Compliance
- Ensure all data activities align with:
- DPR data governance policies
- NDA & Contractual obligations
- Client data requirements
- Ensure AI usage complies with client data restrictions and contracts
- Align with AI governance policies (data privacy, model usage, vendor constraints)
- Help define:
- What data can be shared
- How it can be used (internal vs external)
- Where it should be stored (e.g., warehouse-first approach)
- Support documentation of:
- Data definitions
- Data sources
- Integration logic
Technical Skills
- Working knowledge of Data and AI
- Basic understanding of AI/ML and their capabilities
- Data gathering and quality issues
- Power BI
- Business process and systems thinking
- Map workflows and identify inefficiencies
- Understand system dependencies
- Support integration of AI into existing DPR workflows and systems, from adoption to deployment
- Ability to assist with piloting AI and data solutions on projects, gather user feedback, identify adoption barriers, and refine workflows to ensure tools deliver real-world value.
- Maintain a working knowledge of AI, data capabilities, and limitations to evaluate opportunities realistically. Ask critical questions about data availability, problem fit, and automation value while leveraging common tools such as dashboards and reporting platforms.
Qualifications
Minimum of 4 years of experience in a relevant data analytics/integration delivery role with a strong Power BI background and experience in the construction industry.
Proven track record of managing stakeholder expectations and delivering data solutions aligned with business priorities.
Experience with modern data platforms like Snowflake and Microsoft Fabric.
Experience with mapping, documenting, and analyzing business workflows to identify inefficiencies and gaps.
Ability to translate ambiguous project team requests into clear, actionable use cases with defined data sources and success criteria.
Strong problem-solving skills and ability to troubleshoot complex data issues.
Excellent communication skills, with the ability to work collaboratively in a team environment.
Experience working with or coordinating with overseas teams is a strong plus.
DPR Construction is a forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects for the advanced technology, life sciences, healthcare, higher education and commercial markets. Founded in 1990, DPR is a great story of entrepreneurial success as a private, employee-owned company that has grown into a multi-billion-dollar family of companies with offices around the world.
Working at DPR, you'll have the chance to try new things, explore paths and shape your future. Here, we build opportunity together—by harnessing our talents, enabling curiosity and pursuing our collective ambition to make the best ideas happen. We are proud to be recognized as a great place to work by our talented teammates and leading news organizations like U.S. News and World Report, Forbes, Fast Company and Newsweek.
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Find AI Engineer JobsAI Engineer Job Market in Dallas
Who's Hiring
- Amazon Web Services16

- Deloitte15

- Goldman Sachs11

- Tiger Analytics10

- NTT DATA7

Top Industries Hiring
- Consulting & Professional Services46
- Technology & Software44
- Investment & Asset Management28
- Accounting & Auditing23
- Distribution & Wholesale16
AI Engineer Jobs in Dallas: Frequently Asked Questions
How do I get a ai engineer job in Dallas?
Focus your search on Dallas's three strongest hiring clusters: financial services firms in Uptown and the Arts District, healthcare technology companies in the Medical District, and enterprise software employers along the North Dallas Tollway in Addison and Plano. Candidates who demonstrate hands-on experience with large language models, MLOps pipelines, or production AI systems get the most callbacks in this market. Networking through Dallas-area tech meetups and the Dallas Innovates community also opens doors that job boards alone won't.
Which companies hire ai engineers in Dallas?
Employers hiring ai engineers in Dallas right now include Amazon Web Services, Deloitte, and Goldman Sachs, based on current listings on Migrate Mate as of June 2026. Dallas attracts a mix of Fortune 500 corporations, regional banks and insurers, large hospital systems, and fast-growing technology companies that have relocated their headquarters or major engineering offices to the Metroplex.
Are there remote ai engineer jobs in Dallas?
Yes, and ai engineer roles are among the more remote-friendly positions in tech because the core work, model development, data pipeline engineering, and deployment, happens entirely on a laptop. About 34% of ai engineer openings tied to Dallas are remote or hybrid as of June 2026, reflecting how broadly distributed AI teams have become. The most fully remote openings tend to be in model research and ML platform engineering, while on-site requirements are most common at healthcare systems and regulated financial institutions.
How can I get a ai engineer job in Dallas with little or no experience?
The most realistic entry path in Dallas is through a junior machine learning engineer or data scientist role at one of the Metroplex's many mid-size technology companies or healthcare analytics firms, which tend to hire earlier-career talent than the large corporate headquarters. Building a portfolio with deployed projects on public repositories matters more to Dallas hiring managers than credentials alone. Apprenticeship programs at regional tech accelerators and contract-to-hire positions at Dallas-area staffing firms focused on technology are also solid starting points.
Which industries hire the most ai engineers in Dallas?
The sectors hiring the most ai engineers in Dallas are Consulting & Professional Services, Technology & Software, and Investment & Asset Management, based on current listings on Migrate Mate as of June 2026. Dallas's position as a hub for corporate headquarters, regional banking operations, and one of the largest medical complexes in the country drives consistent AI hiring across all three of those sectors.
See All 185+ AI Engineer Jobs in Dallas
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