1

Associate Ai Engineer Jobs in Raleigh, NC (NOW HIRING)

Senior Advanced AI Research Engineer

Raleigh, NC · On-site

$101K - $139K/yr

Our Data & AI practice brings together more than 45,000 professionals helping clients design ... Associate's degree) in Computer Science, Computer Engineering, or a related field. * Minimum of 5 ...

Industry/Sector Not Applicable Specialism Functional & Industry Technologies Management Level Senior Associate & Summary The Opportunity As a GIS Web AI Developer, Senior Associate, you will play a ...

Associate Software Engineer About Us Advaita Health is committed to a sustainable, integrated model ... Exploring and deploying practical AI and generative AI solutions, including integrating AI ...

New

Showing results 21-40

Associate Ai Engineer information

See Raleigh, NC salary details

$36.6K

$73K

$116.5K

How much do associate ai engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for associate ai engineer in Raleigh, NC is $72,961.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,800.00 and $83,900.00 per year, depending on experience, location, and employer.

What does an Associate AI Engineer do?

An Associate AI Engineer assists in designing, developing, and implementing artificial intelligence models and applications. They typically work under the guidance of senior engineers to build machine learning algorithms, preprocess data, and test AI solutions. Their responsibilities often include writing code, evaluating model performance, and collaborating with data scientists and software developers. This entry-level role provides hands-on experience in AI technologies and helps build a foundation for more advanced engineering positions.

What are the key skills and qualifications needed to thrive as an Associate AI Engineer?

To thrive as an Associate AI Engineer, you need a solid understanding of programming (especially Python), mathematics (linear algebra, probability, statistics), and foundational machine learning concepts, often supported by a degree in computer science or a related field. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and experience with cloud platforms such as AWS or Google Cloud are typically required. Strong problem-solving abilities, effective communication, and a willingness to learn new technologies help distinguish top performers in this role. These skills and qualities are essential for successfully developing, implementing, and maintaining AI solutions in a collaborative and rapidly evolving environment.

What are some common challenges an Associate AI Engineer may face when working on real-world machine learning projects?

As an Associate AI Engineer, you may encounter challenges such as handling imperfect or limited datasets, balancing model performance with computational constraints, and integrating AI solutions into existing products. Collaboration with data scientists, software engineers, and product managers is crucial to refine objectives and ensure technical feasibility. Additionally, keeping up with evolving AI frameworks and best practices can be demanding, but it provides valuable learning opportunities and skill growth.

What is the difference between Associate Ai Engineer vs Data Scientist?

AspectAssociate Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; some certificationsBachelor's or higher in CS, Statistics, or related; often advanced degrees
Work EnvironmentTech companies, startups, R&D teams; focus on AI model developmentResearch labs, tech firms, finance; focus on data analysis and modeling
Employer & Industry UsageAI-focused roles in tech, healthcare, financeData analysis across industries like marketing, finance, healthcare

Associate Ai Engineers typically focus on developing and implementing AI models, often working closely with data and algorithms. Data Scientists analyze large datasets to extract insights and build predictive models. While both roles require programming skills and a background in data or AI, Associate Ai Engineers are more involved in the technical development of AI systems, whereas Data Scientists focus on data analysis and interpretation.

How much do entry level associate AI engineers make?

Entry-level associate AI engineers typically earn between $70,000 and $90,000 annually, depending on location, education, and company size. Starting salaries may also include benefits such as health insurance and opportunities for skill development in machine learning tools and programming languages like Python or TensorFlow.

Is there a demand for associate AI engineers?

There is a strong and growing demand for associate AI engineers as industries increasingly adopt artificial intelligence and machine learning technologies. Entry-level roles often require knowledge of programming languages like Python, familiarity with AI frameworks, and relevant certifications, making it a promising career path for those with technical skills and a background in data science or software development.

What jobs can you get with an associate AI engineer?

An associate AI engineer can qualify for roles such as AI developer, machine learning technician, data analyst, or AI support specialist. These positions typically require knowledge of programming languages like Python, familiarity with AI frameworks, and understanding of data processing. Entry-level roles often involve assisting in developing, testing, and maintaining AI models and systems.

What are the most commonly searched types of Ai Engineer jobs in Raleigh, NC?

The most popular types of Ai Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Associate Ai Engineer jobs?

Cities near Raleigh, NC with the most Associate Ai Engineer job openings:

Infographic showing various Associate Ai Engineer job openings in Raleigh, NC as of August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $72,961 per year, or $35.1 per hour.

Assoc Director, IT Systems Engineering

Gilead Sciences, Inc.

Raleigh, NC • On-site

Full-time

Medical, Dental, Vision, Life, PTO

Posted 17 days ago


Gilead Sciences rating

8.9

Company rating: 8.9 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

9th of 86 rated pharmaceutical


Job description

At Gilead, we're creating a healthier world for all people. For more than 35 years, we've tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer - working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world's biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.
Every member of Gilead's team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we're looking for the next wave of passionate and ambitious people ready to make a direct impact.
We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.
Job Description
Architecture & Platform Strategy
  • Define and evolve the target-state architecture for the self-serve data, AI, and agentic AI platform, aligned to enterprise strategy, data mesh principles, and regulatory requirements
  • Establish enterprise standards and reference architectures for data products, semantic layer services, AI/LLM gateways, agent orchestration, and API- and MCP-based data access
  • Architect the platform layers that let AI systems and agents find, trust, ask, and act on enterprise data - including data product interfaces, semantic context services, and governed write/action patterns
  • Define tiered certification and governance patterns that scale data product trust from registered assets to autonomous-grade, AI-ready products
  • Establish foundational patterns for retrieval, context enrichment, grounding, and tool exposure (RAG, semantic layer, MCP tool surfaces) to support agentic and real-time decisioning use cases

Engineering & Infrastructure
  • Lead engineering of scalable, secure platform infrastructure on AWS (S3, Lake Formation, Glue, EKS, Bedrock, IAM, networking) and Databricks (Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, Mosaic AI)
  • Engineer the agentic AI platform stack: agent runtimes, orchestration, agent identity and access management, action/write contracts, evaluation harnesses, and observability
  • Implement platform engineering best practices: infrastructure-as-code (Terraform), CI/CD, automated testing, environment promotion, and GxP/Part 11-compliant change management
  • Drive operational excellence across reliability, cost management (FinOps for data and AI workloads), observability, and incident response, grounded in SRE and Well-Architected practices
  • Ensure security, data protection, and access governance patterns (fine-grained entitlements, row/column-level controls, audit lineage) meet regulated-industry requirements

Delivery Leadership & Product Management
  • Contribute to the platform product roadmap: define outcomes, prioritize the backlog, and sequence capability delivery against enterprise AI adoption goals
  • Lead delivery across a team of vendor partners, holding the team to clear standards for quality, velocity, and operability
  • Drive build/buy/adopt decisions with rigor - vendor evaluation, kill criteria, and total-cost analysis - and integrate acquired capabilities into a coherent platform experience
  • Define and track platform health and adoption metrics (DORA, reliability SLOs, self-serve adoption, time-to-data-product) and report progress to senior leadership
  • Serve as a trusted advisor and technical leader: mentor engineers, run architecture reviews, and partner with business domains to identify and enable high-value data and AI use cases
  • Communicate architecture and trade-offs crisply to audiences from engineers to Director/VP. stakeholders, simplifying complexity without losing rigor

Basic Qualifications
  • 10+ years in platform engineering, data engineering, or enterprise data/AI platform architecture, including 3+ years leading engineering teams or major platform programs
  • Deep hands-on expertise with AWS data and AI services, including S3, Lake Formation, Glue, EKS, Bedrock, Kinesis/MSK, IAM, and Terraform-based infrastructure automation
  • Strong production experience with Databricks: Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, and workspace/governance administration at enterprise scale
  • Demonstrated experience designing or building agentic AI or LLM-powered systems: agent orchestration, RAG pipelines, LLM gateways, tool/function calling, MCP or comparable protocols, and AI evaluation/observability
  • Proven ability to build resilient, scalable pipelines for high-volume batch and streaming data, with proficiency in SQL and Python (or Scala/Java)
  • Strong understanding of distributed systems, event-driven architecture, workflow orchestration, and API-first integration patterns
  • Experience designing secure, governed, production-grade cloud architectures, including fine-grained access control, lineage, and auditability
  • Track record of delivery leadership: roadmap ownership, backlog management, cross-functional coordination, and shipping platform capabilities that achieve measured adoption
  • Excellent communication skills with the ability to simplify complexity and influence senior decision-makers

Preferred Qualifications
  • Experience in biopharma, life sciences, or other heavily regulated domains, with working knowledge of GxP, 21 CFR Part 11, and computer system validation
  • Background in data mesh or federated data architectures, data product operating models, and domain enablement at enterprise scale
  • Experience with semantic layer technologies, knowledge graphs, metadata/catalog platforms, and data contract frameworks
  • Familiarity with FinOps for data and AI workloads, including cost attribution, chargeback/showback, and LLM token economics
  • Experience managing large vendor/partner ecosystems and running structured vendor evaluations with defined success and kill criteria
  • Product management experience or certification; familiarity with DORA metrics, SPACE framework, and platform-as-a-product operating models
  • AWS Professional (Solutions Architect or Data Analytics) and/or Databricks certifications

The salary range for this position is: $168,980.00 - $218,680.00. Gilead considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans*.
For additional benefits information, visit:
https://www.gilead.com/careers/compensation-benefits-and-wellbeing
* Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.
For jobs in the United States:
Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact ApplicantAccommodations@gilead.com for assistance.
For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster.
NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT
YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT
Gilead Sciences will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, (c) consistent with the legal duty to furnish information; or (d) otherwise protected by law.
Our environment respects individual differences and recognizes each employee as an integral member of our company. Our workforce reflects these values and celebrates the individuals who make up our growing team.
Gilead provides a work environment free of harassment and prohibited conduct. We promote and support individual differences and diversity of thoughts and opinion.
For Current Gilead Employees and Contractors:
Please apply via the Internal Career Opportunities portal in Workday.

What Gilead Sciences employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom