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

RELX

Principal Software Engineer-Agentic AI

Raleigh, NC

$131K - $175K/yr

Are you a collaborative Agentic AI Engineer looking to work for a mission driven global organization? About the team: The Elsevier Healthcare Education (EHE) Data and Content Software Engineering ...

Elsevier

Principal Software Engineer-Agentic AI

Raleigh, NC

$131K - $175K/yr

Are you a collaborative Agentic AI Engineer looking to work for a mission driven global organization? About the team: The Elsevier Healthcare Education (EHE) Data and Content Software Engineering ...

Accenture

AI Native Software Engineer

Raleigh, NC

Tailor and deploy agentic applications across verticals (e.g., finance, healthcare, retail), adapting to domain-specific processes and constraints. * Work closely with client SMEs to translate ...

AstraZeneca

Agentic AI Scientist

Durham, NC · On-site

Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for ... experience with agentic AI design patterns, reinforcement learning. * Extensive industrial ...

AstraZeneca

Agentic AI Scientist

Durham, NC

Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for ... with agentic AI design patterns, reinforcement learning. Extensive industrial experience with AI ...

AstraZeneca

Agentic AI Scientist

Durham, NC · On-site

Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for ... experience with agentic AI design patterns, reinforcement learning. * Extensive industrial ...

AstraZeneca

Agentic AI Scientist

Durham, NC · On-site

Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for ... experience with agentic AI design patterns, reinforcement learning. * Extensive industrial ...

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Showing results 1-20

All JobsAgentic Ai Engineer JobsAgentic Ai Engineer Jobs in Raleigh, NC

Agentic Ai Engineer information

See Raleigh, NC salary details

$37.9K

$98.9K

$133.7K

How much do agentic ai engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for agentic ai engineer in Raleigh, NC is $98,911.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,700.00 and $113,200.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or AI engineering can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries. These roles often require expertise in programming, system architecture, and sometimes leadership or management responsibilities.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles such as AI executives, senior machine learning engineers, or specialized AI researchers earning top-tier salaries. These positions often require advanced skills in deep learning, data science, and experience with large-scale AI systems, along with significant industry expertise and sometimes leadership responsibilities.

What does an agentic AI engineer do?

An agentic AI engineer designs and develops autonomous AI systems capable of making decisions and taking actions independently. They work with machine learning models, reinforcement learning, and AI frameworks to create systems that can adapt and operate in dynamic environments, often requiring knowledge of programming, data analysis, and AI ethics.

What is the salary of agentic AI engineer?

The salary of an agentic AI engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in machine learning and AI development may earn higher compensation, often including benefits and bonuses.
What are popular job titles related to Agentic Ai Engineer jobs in Raleigh, NC? For Agentic Ai Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Agentic Ai Engineer jobs in Raleigh, NC look for? The top searched job categories for Agentic Ai Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Agentic Ai Engineer jobs? Cities near Raleigh, NC with the most Agentic Ai Engineer job openings:
Agentic Ai Engineer jobs near you
Infographic showing various Agentic Ai Engineer job openings in Raleigh, NC as of June 2026, with employment types broken down into 100% Full Time. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $98,911 per year, or $47.6 per hour.
Agentic AI Engineer

Agentic AI Engineer

Cadence Design Systems, Inc.

Cary, NC • On-site

Full-time

Posted 9 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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