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Entry Level Ai Data Engineer Jobs in Raleigh, NC

Infosys

AI/ML Engineer with Generative AI

Raleigh, NC · On-site

The AI/ML Engineer role focuses on leveraging advanced technologies such as generative AI to drive ... scalable data pipelines and APIs to support ML workflows. • Experience in monitoring model ...

Accenture

AI Native Software Engineer

Raleigh, NC

You are An AI Native Engineer with a strong foundation in building cloud-native solutions and hands ... Iterate rapidly based on data, feedback, and changing requirements. Knowledge Sharing * Craft ...

TEKsystems

Principal AI Engineer

Raleigh, NC · On-site +1

$75 - $100/hr

... data preprocessing, feature engineering, and model evaluation. • Troubleshoot and debug AI models and applications in a mono-repo settings. • Document AI models, processes, and workflows.

NIC MAP

Principal Software Engineer

Raleigh, NC · On-site

$165K - $185K/yr

... for data engineering. We pick the right tool for the problem. * Use AI tooling daily (Claude Code, Cursor, AI agents, MCP connectors) to ship faster and eliminate toil. * Architect and deliver ...

NIC MAP

Principal Software Engineer

Raleigh, NC · On-site +1

$165K - $185K/yr

... for data engineering. We pick the right tool for the problem. * Use AI tooling daily (Claude Code, Cursor, AI agents, MCP connectors) to ship faster and eliminate toil. * Architect and deliver ...

VAST Data

DevOps Engineer (East Coast)

Raleigh, NC · On-site +1

$51.25 - $70.25/hr

... Data is the data platform company for the AI era. We are building the enterprise software ... Engineer position is a sales engineering operations role and is an integrated part of our sales ...

RoviSys

Entry Level Engineer/Developer

Holly Springs, NC · On-site

$80K - $82K/yr

Architect solutions using the appropriate technologies from database to AI to User Interface tools ... Entry Level Position: College Graduate - 2 years experience Below are the career paths we ...

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All JobsAi Data Engineer JobsEntry Level Ai Data Engineer JobsEntry Level Ai Data Engineer Jobs in Raleigh, NC

Entry Level Ai Data Engineer information

See Raleigh, NC salary details

$43.3K

$126.1K

$172.5K

How much do entry level ai data engineer jobs pay per year?

As of Jun 13, 2026, the average yearly pay for entry level ai data engineer in Raleigh, NC is $126,095.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,300.00 and $133,700.00 per year, depending on experience, location, and employer.

What are some common challenges faced by entry level AI data engineers in their first year on the job?

Entry level AI data engineers often encounter challenges such as learning to manage large datasets efficiently, understanding complex data pipelines, and adapting to rapidly evolving AI tools and frameworks. Collaborating with data scientists and senior engineers can be initially overwhelming, but it's a great opportunity to learn industry best practices. Balancing multiple tasks like data cleaning, preprocessing, and supporting model deployment while honing programming skills is typical. Proactively seeking feedback and asking questions is key to overcoming these hurdles and growing in the role.

What are the key skills and qualifications needed to thrive as an Entry Level AI Data Engineer, and why are they important?

To thrive as an Entry Level AI Data Engineer, you need proficiency in programming languages like Python or Java, a foundational understanding of data structures and algorithms, and a relevant degree in computer science or a related field. Familiarity with data processing frameworks (e.g., Hadoop, Spark), cloud platforms (e.g., AWS, Azure), and basic knowledge of machine learning libraries are typically expected. Strong analytical thinking, attention to detail, and effective teamwork set outstanding candidates apart. These skills and qualities are crucial for building reliable data pipelines, supporting AI models, and ensuring efficient collaboration within technical teams.

What is the difference between Entry Level Ai Data Engineer vs Data Analyst?

AspectEntry Level Ai Data EngineerData Analyst
Required SkillsBasic programming, data modeling, understanding of AI/ML conceptsData visualization, statistical analysis, SQL proficiency
CertificationsPython, SQL, entry-level AI/ML coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, AI startups, data-driven teamsBusiness, marketing, finance sectors
Job FocusBuilding AI models, data pipelines, integrating AI solutionsInterpreting data, creating reports, supporting decision-making

While both roles involve working with data, Entry Level Ai Data Engineers focus on developing AI models and data infrastructure, whereas Data Analysts primarily analyze data to generate insights. The former requires some knowledge of AI/ML, while the latter emphasizes statistical and visualization skills.

What is an Entry Level AI Data Engineer?

An Entry Level AI Data Engineer is a professional who helps build and maintain data pipelines and infrastructure to support artificial intelligence and machine learning applications. They typically work with large volumes of data, ensuring it is properly collected, cleaned, and organized for analysis. Their responsibilities may include working with databases, data processing tools, and cloud platforms, as well as collaborating with data scientists and software engineers to enable AI-driven solutions. This role is ideal for recent graduates or those new to the field, providing foundational experience in data engineering within the context of AI.
What are the most commonly searched types of Ai Data Engineer jobs in Raleigh, NC? The most popular types of Ai Data Engineer jobs in Raleigh, NC are:
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What cities near Raleigh, NC are hiring for Entry Level Ai Data Engineer jobs? Cities near Raleigh, NC with the most Entry Level Ai Data Engineer job openings:
Entry Level Ai Data Engineer jobs near you
Agentic AI Engineer

Agentic AI Engineer

Cadence Design Systems, Inc.

Cary, NC • On-site

Full-time

Posted 10 days ago

Job description

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.
Agentic AI Engineer
Role Summary
Cadence is hiring early-career Agent AI Engineers to join our applied AI team building agentic systems for silicon design. You will work alongside senior AI engineers and chip-design domain experts on the core technical pillars of Cadence's agentic stack: training and adapting models for engineering tasks, engineering high-quality design context (RAG, prompt scaffolds, retrieval pipelines), and tuning the knowledge graphs and vector/graph databases that ground our agents. From day one you will be writing production code that lands in customer-facing AI products and directly accelerates how the world designs chips.
What You Will Do
  • Model Development. Train, fine-tune, distill, and evaluate LLMs / SLMs and embedding models for EDA-specific tasks. Hands-on with LoRA / PEFT, instruction tuning, preference optimization (DPO/GRPO), and rigorous eval harnesses for code and reasoning.
  • Design Context Engineering. Build the retrieval pipelines, prompt scaffolds, and tool-calling specs that feed Cadence agents the right design context (RTL, scripts, logs, reports, methodology docs) at the right token budget. Optimize for accuracy, latency, and cost.
  • Knowledge Graph & Database Tuning. Design schemas, tune ingestion, and optimize queries for graph DBs (Neo4j, ArangoDB, NebulaGraph) and vector stores (Qdrant, Weaviate, pgvector, Chroma). Keep retrieval fast, accurate, and scoped to the right design hierarchy.
  • Agent Building Blocks. Implement and harden agent tools, memory, multi-hop reasoning patterns, and guardrails. Triage production failures and iterate.
  • Data Pipelines. Curate, clean, and label datasets from EDA artifacts (RTL, waveforms, logs, reports, schematics). Build synthetic-data and self-improvement loops where appropriate.
  • Evaluation & Telemetry. Build offline benchmarks and online metrics. Help define what 'good' looks like for chip-design agents and keep regressions out of main.
  • Collaborate & Learn. Pair with senior AI engineers, BU teams, and silicon domain experts. Learn the EDA flow as you go - we'll invest in you if you invest in the craft.

Must-Have Qualifications
  • BS / MS / PhD in CS, EE, ECE, AI/ML, or a closely related field (graduating in 2025-2026; recent grads also welcome).
  • Strong fundamentals in deep learning, transformers, and modern LLM mechanics (attention, tokenization, context windows, decoding).
  • Practical hands-on experience (coursework, internships, OSS, or serious side projects) with at least TWO of: LLM fine-tuning, RAG / retrieval, agentic frameworks, knowledge graphs, vector databases.
  • Solid Python engineering: comfortable with PyTorch and Hugging Face; writes clean, tested, version-controlled code.
  • Curiosity about silicon / chip design and willingness to learn a deep technical domain on the job.
  • Strong written and verbal communication; bias to ship working code over perfect plans.

Nice-to-Have / Bonus
  • Prior internship in AI/ML at a product company or research lab with shipped artifacts.
  • Hands-on with at least one agentic framework: LangGraph, AutoGen, Cursor SDK, Claude Code, MCP-based tool-calling stacks.
  • Experience with graph DBs (Neo4j, ArangoDB, NebulaGraph) and / or vector DBs (Qdrant, Weaviate, pgvector, Chroma, Milvus).
  • ML systems / infra exposure: vLLM, TGI, Triton, distributed training, GPU performance tuning, quantization.
  • Coursework or projects in compilers, formal methods, hardware description languages (Verilog/SystemVerilog/Chisel), or EDA tools.
  • Publications, OSS contributions, or competitive ML records (Kaggle medals, MLPerf, agent benchmarks, hackathon wins).

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