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Llm Developer Jobs in Emmaus, PA (NOW HIRING)

Hudson Manpower

Sr Full stack Java Developer

Allentown, PA · On-site

$60 - $65/hr

AI Full Stack Java Developer * Designed and developed scalable AI-powered full-stack applications ... Worked with OpenAI/Azure OpenAI or equivalent LLM platforms , embedding models, vector search, and ...

Mondo

Sr. Dev SecOps Architect

Danboro, PA · On-site

$75 - $90/hr

Bachelor's degree in Computer Science, Information Security, Engineering, or a related technical field. Preferred Qualifications: * Experience securing AI/LLM-powered applications or agentic systems.

Allere

Data Security Architect

Allentown, PA

$63 - $81/hr

... LLM pipelines, secure vector stores, and legacy data remediation. This individual will collaborate closely with Security Engineering, Data Governance, Cloud Ops, and AI/ML teams to secure data ...

All JobsLlm Developer JobsLlm Developer Jobs in Emmaus, PA

Llm Developer information

See Emmaus, PA salary details

$24

$48

$76

How much do llm developer jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for llm developer in Emmaus, PA is $48.21, according to ZipRecruiter salary data. Most workers in this role earn between $37.88 and $58.46 per hour, depending on experience, location, and employer.

What does an LLM Developer do?

An LLM Developer designs, fine-tunes, and implements large language models (LLMs) for various applications, such as chatbots, content generation, and AI-driven tools. They work with machine learning frameworks, optimize model performance, and ensure efficient deployment. This role requires expertise in natural language processing (NLP), deep learning, and programming languages like Python.

What are the key skills and qualifications needed to thrive as an LLM Developer?

To excel as an LLM Developer, you need strong expertise in natural language processing (NLP), deep learning frameworks, and programming languages such as Python, typically supported by a degree in computer science or a related field. Familiarity with machine learning libraries (like TensorFlow or PyTorch), cloud computing platforms, and experience with prompt engineering or fine-tuning large language models is crucial. Excellent problem-solving abilities, collaboration, and effective communication skills help you design solutions and work efficiently within multidisciplinary teams. These qualifications are essential for successfully building, deploying, and optimizing large language models that drive impactful AI applications.

What is the role of a large language model developer?

A large language model developer designs, trains, and fine-tunes AI models that understand and generate human language. They work with machine learning frameworks, manage large datasets, and optimize models for accuracy and efficiency, often requiring knowledge of programming, deep learning, and natural language processing techniques.

What cities near Emmaus, PA are hiring for Llm Developer jobs?

Cities near Emmaus, PA with the most Llm Developer job openings:

Llm Developer jobs near you
Infographic showing various Llm Developer job openings in Emmaus, PA as of August 2026, with employment types broken down into 77% Full Time, 9% Part Time, and 14% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $100,274 per year, or $48.2 per hour.

AI Agent Developer QA Specialization

Warren, NJ • On-site

Accord Technologies Inc.
51 - 200 employees
Learn more about Accord Technologies Inc.external

Contractor

Re-posted 18 days ago

Job description

AI Agent Developer – QA Specialization
Location: Warren, NJ
Position type: W2 contract
 

Job Summary

We are seeking a QA domain expert with strong experience in AI development to design and build advanced QA Agents. This role is ideal for a QA engineer/developer who has transitioned to AI/ML, Large Language Models (LLMs), and agentic architectures. You will be responsible for architecting, implementing, and optimizing AI agents that automate, augment, and scale quality assurance processes within our engineering teams.

Key Responsibilities

  • Analyze QA workflows to design agent architectures that automate requirement analysis, test generation, defect triage, and reporting.
  • Build, fine-tune, and maintain QA agents using frameworks such as LangChain, OpenAI, LlamaIndex, or custom RL approaches.
  • Engineer prompts and context strategies for LLM-powered test case generation, regression analysis, and intelligent reporting.
  • Integrate agents with code repositories, CI/CD systems, test management platforms, and communication tools.
  • Collaborate with QA, development, and AI/ML teams to collect requirements and continually improve agent performance.
  • Implement agent validation, test coverage measurement, and reliability evaluation for agent-driven QA flows.
  • Contribute to the continuous evolution of self-healing and adaptive QA agent features.
  • Document agent design, workflows, evaluation metrics, and operational guidelines.

Required Skills & Qualifications

  • Bachelor’s or Master’s in Computer Science, Engineering, or related field.
  • 3+ years in QA engineering, automation, or SDET roles.
  • 1+ years hands-on developing AI/LLM-based applications or agents (preferably for process automation or software quality).
  • Strong programming skills: Python (must); knowledge of JavaScript/TypeScript, Java, or Go is an advantage.
  • Proven experience with one or more of: LangChain, OpenAI API, LlamaIndex, Vertex AI, or similar agent and LLM frameworks.
  • Experience integrating AI solutions with DevOps toolchains (Jenkins, GitHub, Jira, etc.).
  • Deep understanding of software testing lifecycle, automation frameworks, and QA metrics.
  • Clear communication skills with an ability to document and explain agent logic and technical rationale.

Bonus/Preferred Skills

  • Experience designing agents for software quality–test generation, autonomous triage, or regression analysis.
  • Familiarity with RAG (Retrieval-Augmented Generation) and prompt tooling.
  • Knowledge of agent frameworks (e.g., CrewAI, AutoGen, or similar).
  • Contributions to open-source QA-AI tools or published research in autonomous QA.