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Llm Developer Jobs in Slatington, 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 ...

Allere

Data Security Architect

Allentown, PA · On-site

$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 Slatington, PA

Llm Developer information

See Slatington, PA salary details

$20

$39

$62

How much do llm developer jobs pay per hour?

As of Aug 27, 2026, the average hourly pay for llm developer in Slatington, PA is $39.66, according to ZipRecruiter salary data. Most workers in this role earn between $31.15 and $48.08 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 Slatington, PA are hiring for Llm Developer jobs?

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

Llm Developer jobs near you

Sr Full stack Java Developer

Allentown, PA • On-site

Hudson Manpower
See more jobs at Hudson Manpowerexternal

$60 - $65/hr

Contractor

Posted 6 days ago

Job description

AI Full Stack Java Developer
  • Designed and developed scalable AI-powered full-stack applications using Java, Spring Boot, React/Angular, REST APIs, and cloud-native technologies.
  • Integrated Generative AI and Large Language Models (LLMs) into enterprise applications to deliver intelligent search, content generation, recommendation, summarization, and conversational capabilities.
  • Built AI-enabled backend services using Java, Spring Boot, Spring AI, LangChain/LangGraph concepts, and RESTful APIs, ensuring secure and maintainable application architecture.
  • Developed Retrieval-Augmented Generation (RAG) solutions by integrating LLMs with enterprise documents, knowledge bases, vector databases, and semantic search.
  • Implemented prompt engineering, prompt templates, response validation, context management, and AI guardrails to improve accuracy, consistency, and reliability of AI-generated responses.
  • Developed responsive and reusable frontend components using React/Angular, TypeScript, JavaScript, HTML5, and CSS3, integrating them with AI-enabled backend services.
  • Designed microservices using Spring Boot, Spring Cloud, API Gateway, and service-to-service communication for highly scalable distributed applications.
  • Developed and consumed REST and event-driven APIs, integrating third-party AI platforms, enterprise systems, databases, and external services.
  • Worked with OpenAI/Azure OpenAI or equivalent LLM platforms, embedding models, vector search, and AI APIs into production applications.
  • Implemented vector-based knowledge retrieval using technologies such as Pinecone, Azure AI Search, Elasticsearch, or PostgreSQL with pgvector.
  • Designed data persistence solutions using PostgreSQL, MySQL, MongoDB, and Redis, selecting appropriate storage mechanisms based on application requirements.
  • Applied Spring Security, OAuth 2.0, JWT, RBAC, and API security practices to protect enterprise and AI-powered applications.
  • Implemented asynchronous and event-driven processing using Kafka, RabbitMQ, or cloud messaging services for high-volume workloads.
  • Containerized applications using Docker and deployed microservices to Kubernetes and cloud platforms such as AWS, Azure, or GCP.
  • Developed CI/CD pipelines using Jenkins, Maven, Git, GitHub/GitLab, and automated deployment workflows.
  • Implemented automated unit, integration, API, and end-to-end testing using JUnit, Mockito, REST Assured, Selenium, Playwright, or Cypress.
  • Added observability through logging, metrics, distributed tracing, health checks, and application monitoring, helping identify performance and AI-service issues.
  • Optimized application performance through caching, database tuning, API optimization, asynchronous processing, and efficient LLM/API utilization.
  • Collaborated with product managers, architects, data scientists, QA engineers, and DevOps teams to transform business requirements into production-ready AI solutions.

Requirements
  • 5+ years of professional software development experience with strong expertise in Java and Spring Boot.
  • Strong hands-on experience building full-stack applications using Java, Spring Boot, REST APIs, React or Angular, JavaScript, and TypeScript.
  • Experience designing and developing microservices-based, scalable, and cloud-native applications.
  • Practical experience integrating Generative AI, Large Language Models (LLMs), and AI APIs into enterprise applications.
  • Strong understanding of RAG architecture, embeddings, vector databases, semantic search, prompt engineering, and LLM orchestration.
  • Experience working with OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar AI platforms.
  • Knowledge of Spring AI, LangChain/LangGraph, or comparable AI application frameworks is highly desirable.
  • Experience developing and consuming RESTful APIs, JSON-based services, and third-party integrations.
  • Strong database experience with PostgreSQL, MySQL, MongoDB, Redis, or similar technologies.
  • Experience with Kafka, RabbitMQ, or other event-driven messaging platforms.
  • Hands-on experience with Docker, Kubernetes, CI/CD, Jenkins, Maven, Git, and cloud deployment.

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