AI Data Engineer Jobs in Tennessee
AI Data Engineer jobs in Tennessee are in active demand, with concentrated hiring in healthcare IT, logistics, and financial services across experience levels from entry-level to senior engineer. Nashville, Memphis, and Chattanooga are the primary hiring hubs, home to established employers like HCA Healthcare, FedEx, and Unum Group, which maintain substantial data and analytics teams in the state. The most sought-after specialties include cloud data pipeline development, ML infrastructure, and real-time analytics engineering. Find a role that fits below and apply directly.
Find AI Data Engineer JobsOverview
Showing 5 of 65+ AI Data Engineer jobs











INTRODUCTION
The Director, Data Science & AI Engineering will lead the development and execution of the Firm’s enterprise data science, analytics, and AI engineering strategy. This role is responsible for building and managing a multidisciplinary team of Data Scientists, Data Analysts, and MLOps / AI Engineers focused on delivering innovative, production-ready AI solutions that support the Firm’s legal and business operations. Key responsibilities include overseeing the design, implementation, and optimization of LLM-powered applications, retrieval-augmented generation (RAG) systems, AI agents, custom models, advanced analytics, and business intelligence platforms that provide actionable matter, financial, and operational insights to firm leadership.
This position serves as a strategic and hands-on leadership role within a rapidly evolving AI environment, responsible for establishing scalable architecture, governance, evaluation standards, security practices, and operational frameworks appropriate for a highly regulated professional services organization. The Director will work closely with the Knowledge Management & Innovation function and other firm stakeholders to translate legal and operational needs into practical AI-driven solutions that enhance efficiency, decision-making, and service delivery across the Firm.
KEY RESPONSIBILITIES
Leadership
- Design and implement the operational framework, team structure, delivery processes, and performance metrics for the firm’s Data Science & AI Engineering function.
- Recruit, develop, and lead a high-performing multidisciplinary team of Data Scientists, Data Analysts, and MLOps/AI Engineers, establishing strong technical and cultural standards.
- Oversee day-to-day team operations, including strategic planning, prioritization, project delivery, performance management, mentorship, and employee development.
- Foster a collaborative, innovative, and business-focused culture centered on delivering practical AI and analytics solutions that support legal and operational outcomes.
Build & Lead Internal AI Platforms and Solutions
- Design, develop, and deploy internal AI applications leveraging firm-approved large language models (LLMs), with a focus on scalability, evaluation, observability, and cost efficiency.
- Lead the development and management of the firm’s retrieval-augmented generation (RAG) capabilities, including ingestion pipelines, embeddings, vector and hybrid search, re-ranking, and citation-supported response generation across firm knowledge and matter data.
- Oversee integrations between AI applications and internal business systems, including document management, matter management, financial, timekeeping, and knowledge management platforms, utilizing secure and governed integration frameworks such as Model Context Protocol (MCP).
- Develop and operationalize AI-driven workflows and agent-based solutions that support legal and business processes, incorporating appropriate governance, controls, traceability, and human oversight.
- Direct model development, fine-tuning, evaluation, and optimization initiatives utilizing proprietary firm data while ensuring compliance with confidentiality, privilege, intellectual property, and security requirements.
- Lead the firm’s analytics and reporting initiatives, including data modeling, warehouse/lakehouse strategy, and the development of dashboards and business intelligence tools that provide actionable operational, financial, staffing, and AI utilization insights to firm leadership.
MLOps, Engineering Excellence, and Governance
- Establish and oversee core AI engineering and operational standards, including source control, CI/CD processes, infrastructure-as-code, observability, environment management, evaluation frameworks, and production support practices.
- Lead and maintain scalable MLOps/LLMOps capabilities, including prompt and model versioning, automated testing, performance monitoring, drift detection, latency and cost tracking, and incident management processes.
- Partner with Information Security, IT, Privacy, Risk, and the Office of General Counsel to ensure AI solutions comply with firm standards related to confidentiality, privilege, client obligations, data governance, and regulatory requirements.
- Support the development and execution of the firm’s AI governance framework, including acceptable use standards, vendor and model evaluation processes, testing protocols, and risk management practices.
- Evaluate and recommend build-versus-buy strategies for AI and technology solutions, leveraging commercial platforms where appropriate and developing custom solutions where the firm can achieve strategic or operational advantage.
Collaboration Across the Firm
- Collaborate closely with Knowledge Management & Innovation leadership to align AI development initiatives with practice group priorities, business needs, and user adoption strategies.
- Partner with attorneys, practice groups, and business stakeholders throughout the solution development lifecycle to ensure AI tools and workflows address operational and client service needs effectively.
- Communicate technical concepts, architectural decisions, and implementation trade-offs clearly and effectively to business and legal stakeholders.
- Represent the firm in interactions with vendors, clients, industry groups, peer organizations, and the broader legal AI community to support innovation, strategic partnerships, and talent development.
REQUIRED EDUCATION, KNOWLEDGE & EXPERIENCE
- Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Data Science, or a related quantitative field, or equivalent combination of education and relevant professional experience. Advanced degrees preferred.
- 10+ years of progressive experience in data science, machine learning, AI engineering, or a related technical discipline, including demonstrated leadership experience building and managing high-performing technical teams.
- Proven success designing, deploying, and supporting production AI/ML solutions, including large language model (LLM) applications, retrieval-augmented generation (RAG) systems, and agent-based workflows.
- Strong technical foundation with the ability to evaluate system architecture, engineering approaches, model performance, and technical design decisions across AI and analytics platforms.
- Deep understanding of modern AI technologies and architectures, including foundation models, embeddings, vector databases, hybrid search, RAG methodologies, agent frameworks, Model Context Protocol (MCP), prompt engineering, model evaluation, fine-tuning, and operational scalability considerations.
- Experience establishing and supporting MLOps/LLMOps practices, including cloud infrastructure, deployment automation, monitoring, security, and operational governance.
- Demonstrated experience leading enterprise analytics and business intelligence initiatives, including the development of executive-facing dashboards and reporting solutions that support strategic decision-making.
- Strong leadership, organizational, and problem-solving skills, with the ability to operate effectively in fast-paced, evolving, and highly collaborative environments.
- Excellent written and verbal communication skills, including the ability to communicate complex technical concepts, AI risks, and architectural decisions clearly to executive leadership, attorneys, and non-technical stakeholders.
- Sound judgment regarding AI governance, privacy, security, confidentiality, and ethical considerations associated with deploying AI technologies in regulated and data-sensitive environments.
PREFERRED SKILLS & QUALIFICATIONS
- Experience within the legal, professional services, financial services, or another highly regulated, document-intensive industry environment. Legal education or prior legal industry experience is a plus.
- Familiarity with legal technology and enterprise data platforms, including document management systems, matter and timekeeping systems, knowledge management platforms, eDiscovery technologies, and litigation support tools.
- Hands-on experience with AI platforms and tooling from providers such as OpenAI, Anthropic, Google, Microsoft, and open-source AI ecosystems, including familiarity with legal-specific AI platforms such as Harvey, CoCounsel, and Legora.
- Active participation in the AI engineering, machine learning, or applied research community through publications, speaking engagements, open-source contributions, or established industry networks.
Physical Requirements
- Ability to sit and stand for extended periods.
- Ability to lift up to 15 pounds.
Qualified applicants with arrest and conviction records will be considered for the position in accordance with the California Fair Chance Act.
The expected salary range for this position is $290,000 - $440,000. Final compensation will be determined based on several factors, including but not limited to, relevant experience, qualifications, skill set, and geographic location.
Pillsbury Winthrop Shaw Pittman LLP is an Equal Opportunity Employer.
If you require an accommodation in order to apply for a position, please contact us at PillsburyWorkday@pillsburylaw.com.
See All 65 AI Data Engineer Jobs in Tennessee
Find roles in Tennessee that match your experience and apply in just a few clicks.
Find AI Data Engineer JobsAI Data Engineer Jobs by City in Tennessee
Where Tennessee roles are concentrated, by current openings.
AI Data Engineer Job Market in Tennessee
A snapshot from current Tennessee openings, updated as new roles post.
Who's Hiring
- HCA Healthcare8

- Amazon6

- Schneider Electric5

- Capgemini4

- Starbucks4

Top Industries Hiring
- Technology & Software13
- Human Resources8
- Healthcare & Medical Services8
- Manufacturing6
- Investment & Asset Management6
What Tennessee Employers Look For
The qualifications that appear most often in AI data engineer jobs across Tennessee.
- Bachelor's or master's degree in computer science, data engineering, or a related technical field
- Proficiency in Python or Scala for building and maintaining large-scale data pipelines
- Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud
- Familiarity with data warehousing tools like Snowflake, Databricks, or Apache Spark
- Experience designing and deploying machine learning infrastructure or MLOps workflows
- Strong understanding of SQL and experience working with both structured and unstructured data
AI Data Engineer Jobs in Tennessee: Frequently Asked Questions
How do you become a ai data engineer in Tennessee?
Most ai data engineers in Tennessee enter the field through a bachelor's degree in computer science, information systems, or a related discipline, followed by hands-on experience with data pipeline tools and cloud platforms. Tennessee does not require a state-issued license for this role. Employers like HCA Healthcare and Unum Group recruit from strong regional programs at Vanderbilt University, Tennessee Tech, and the University of Tennessee, and many candidates strengthen their candidacy with cloud certifications from AWS or Google.
How much do AI data engineers make in Tennessee?
AI data engineers in Tennessee earn a median of about $100,330 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $60,200 for the lowest 10% to over $156,160 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai data engineers in Tennessee?
Employers hiring ai data engineers in Tennessee right now include HCA Healthcare, Amazon, and Schneider Electric, based on current listings on Migrate Mate as of June 2026. Tennessee's large healthcare, logistics, and insurance sectors create steady demand for data engineering talent across the state.
Which Tennessee cities have the most ai data engineer jobs?
Nashville, Memphis, and Brentwood have the most ai data engineer openings in Tennessee. Nashville dominates due to its dense concentration of healthcare IT and financial services companies, while Memphis draws demand from major logistics and supply chain operations, and Chattanooga has grown as a technology and advanced manufacturing hub anchored by corporate and regional employers.
Are there remote ai data engineer jobs in Tennessee?
Yes, and more than most fields. About 20% of ai data engineer openings tied to Tennessee are remote or hybrid as of June 2026, reflecting how much of the work involves cloud infrastructure and code rather than on-site systems. Pipeline development, data modeling, and ML infrastructure roles are the most likely to be fully remote.
How can I get hired as a ai data engineer in Tennessee with little or no experience?
The most realistic entry path is a junior or associate data engineer role, often reached by building a portfolio of data pipeline and cloud projects through personal or open-source work. Tennessee employers like HCA Healthcare and regional fintech companies hire entry-level candidates from adjacent roles such as data analyst, BI developer, or software developer. Earning an entry-level cloud certification from AWS or Google, or completing a data engineering bootcamp tied to a Nashville or Knoxville tech community, meaningfully improves early candidacy.
Where can I find and apply to ai data engineer jobs in Tennessee?
You can find and apply to ai data engineer jobs in Tennessee on Migrate Mate, which lists current openings from employers hiring in the state. Search the available roles, find the ones that fit your background and preferences, and apply directly.
See All 65 AI Data Engineer Jobs in Tennessee
Find roles in Tennessee that match your experience and apply in just a few clicks.
Find AI Data Engineer Jobs