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Generative Ai Developer Jobs in Springfield, PA (NOW HIRING)

SID Global Solutions

AI Lead Developer

Exton, PA

$57 - $74.50/hr

Exton, PA Onsite Employment Type: Full-Time We are seeking a hands-on AI Lead Developer to architect, build, and deploy enterprise-scale Agentic AI, Generative AI, and Multi-Agent Solutions. This ...

Prophecy Technologies

Scrum Master AI

Philadelphia, PA · On-site

$52 - $69.25/hr

... engineering teams Support delivery of AI/ML and Generative AI initiatives Ensure Agile best practices are followed across teams Communicate project status to stakeholders and leadership

SID Global Solutions

AI Lead Developer

Exton, PA · On-site

$57 - $74.50/hr

AI Lead Developer - Agentic AI & GenAI Solutions Location: Exton, PA Onsite Employment Type ... Design and develop enterprise-grade Agentic AI and Generative AIsolutions. * Build multi-agent ...

Holtec International

AI Engineer

Camden, NJ · On-site

$120K - $140K/yr

The AI Engineer designs and builds intelligent applications powered by Large Language Models (LLMs ... Design, develop, and deploy Generative AI solutions using modern LLMs and enterprise AI platforms.

Staffingine LLC

AI Engineer

Malvern, PA · On-site

$42 - $52/hr

AI Engineer Job Location: Malvern, PA Job Type: Contract * Design, build, and optimize AI agents ... Work with Amazon Bedrock to integrate and orchestrate generative AI services * Collaborate with ...

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How much do generative ai developer jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for generative ai developer in Springfield, PA is $42.72, according to ZipRecruiter salary data. Most workers in this role earn between $22.21 and $51.68 per hour, depending on experience, location, and employer.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What are the key skills and qualifications needed to thrive as a generative AI developer?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.
What cities near Springfield, PA are hiring for Generative Ai Developer jobs? Cities near Springfield, PA with the most Generative Ai Developer job openings:
Generative Ai Developer jobs near you

Generative AI Engineer- Philadelphia, PA

QTech US Inc

Philadelphia, PA • On-site

Other

Posted 5 days ago

Job description

Job Title: Generative AI Engineer
Location: Philadelphia, PA - Hybrid
Looking for W2 candidates. No C2C

Job Summary:
Philadelphia Gas Works (PGW) is seeking an experienced Generative AI Engineer / On-Prem LLM & Vector Database Consultant to design, deploy, and optimize an enterprise-grade on-premises Large Language Model (LLM) and Vector Database solution in a secure environment. The ideal candidate will possess strong expertise in open-source LLM deployment, Retrieval-Augmented Generation (RAG), vector databases, semantic search, and enterprise AI infrastructure while ensuring data privacy, security, and high-performance inference in private or air-gapped environments.
Key Responsibilities:
Design and implement an on-premises LLM architecture for secure enterprise AI applications.
Deploy and optimize open-source LLMs including Meta Llama 3, Mistral, and Mixtral.
Build and implement Retrieval-Augmented Generation (RAG) pipelines.
Design, configure, and manage Vector Database solutions for semantic search.
Develop Python-based LLM inference, orchestration, prompt engineering, and integrations.
Optimize model performance using CPU inference, model quantization, and inference tuning.
Generate and manage embeddings, metadata filtering, and semantic search workflows.
Implement enterprise-grade authentication, authorization, access controls, and audit logging.
Ensure compliance with secure, private, and air-gapped deployment requirements.
Deliver deployment architecture, technical documentation, and knowledge transfer sessions.
Build a working prototype integrating LLM + Vector Database + RAG Pipeline.
Collaborate with engineering teams to deploy scalable AI infrastructure.
Required Skills:
Strong experience deploying Open-Source LLMs (Meta Llama 3, Mistral, Mixtral).
Proficient in Python, Prompt Engineering, LLM Inference, Model Orchestration, and AI Integration.
Experience with CPU-based inference, Model Quantization, and performance optimization.
Hands-on experience with Vector Databases (Qdrant, Chroma, Milvus, pgvector).
Proven expertise in building Retrieval-Augmented Generation (RAG) pipelines.
Experience with Embeddings, Metadata Filtering, and Semantic Search.
Strong knowledge of Enterprise Security, Data Privacy, and Air-Gapped Deployments.
Experience implementing Authentication, Authorization, Access Controls, and Audit Logging.
Preferred Qualifications:
Experience with LangChain and/or LlamaIndex.
Knowledge of Rust, Go, or C++.
Experience with Docker and Kubernetes for on-prem deployments.
Familiarity with inference frameworks:
o vLLM
o llama.cpp
o Hugging Face Transformers
Experience working in regulated or enterprise environments.
Experience designing enterprise AI reference architectures.
Best Regards:
Tejaswani R.
Phone: +1-
Email:

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