ZipRecruiter

Log In

1

Ai Rag Jobs in Erie, PA (NOW HIRING)

Sedgwick

Senior Engineer - LLMOps & MLOps

North East, PA · On-site +1

$96K - $132K/yr

You will be responsible for the "Ops" of AI: ensuring that LLM applications, RAG pipelines, and traditional ML models are deployable, observable, and scalable in a multi-cloud environment. Key ...

All JobsAi Rag JobsAi Rag Jobs in Erie, PA

Ai Rag information

See Erie, PA salary details

$31K

$56.4K

$80.9K

How much do ai rag jobs pay per year?

As of Aug 6, 2026, the average yearly pay for ai rag in Erie, PA is $56,430.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,500.00 and $63,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What job categories do people searching Ai Rag jobs in Erie, PA look for? The top searched job categories for Ai Rag jobs in Erie, PA are:
What cities near Erie, PA are hiring for Ai Rag jobs? Cities near Erie, PA with the most Ai Rag job openings:
Ai Rag jobs near you
Infographic showing various Ai Rag job openings in Erie, PA as of August 2026, with employment types broken down into 71% Full Time, 26% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $56,430 per year, or $27.1 per hour.

Senior and Applied/Agentic AI Engineer

Sedgwick

North East, PA

$96K - $132K/yr

Other

Re-posted 26 days ago

Sedgwick rating

7.6

Company rating: 7.6 out of 10

Based on 320 frontline employees who took The Breakroom Quiz

207th of 301 rated insurance

Job description

By joining Sedgwick, you'll be part of something truly meaningful. It's what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there's no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America's Greatest Workplaces National Top Companies

Certified as a Great Place to Work

Fortune Best Workplaces in Financial Services & Insurance

Senior and Applied/Agentic AI Engineer

Job Responsibilities

Lead the architecture and delivery of enterprise-grade LLM and agentic AI systems that transform claims, risk, and operational workflows.

Define technical strategy for retrieval-augmented generation (RAG), multi-agent orchestration, and autonomous workflow automation.

Design and implement advanced agentic systems capable of planning, reasoning, tool selection, execution, reflection, and recovery.

Architect stateful, memory-aware AI systems that manage long-running claims processes across multiple touchpoints.

Build multi-agent collaboration models that coordinate coverage analysis, document validation, fraud signals, compliance checks, and decision support.

Establish orchestration frameworks that manage task routing, context persistence, structured outputs, and failure handling.

Design secure tool integration layers connecting agents to claims systems, policy platforms, data warehouses, document repositories, and external data services.

Implement deterministic guardrails, schema validation, and output verification pipelines to reduce hallucination and execution risk.

Lead development of document intelligence systems leveraging LLMs for summarization, entity extraction, discrepancy detection, and structured data reconstruction.

Define prompt engineering standards and reusable reasoning templates for consistent, domain-aware outputs.

Oversee embedding strategies, vector indexing architecture, retrieval optimization, and knowledge grounding approaches.

Design evaluation frameworks to measure reasoning depth, workflow completion accuracy, hallucination rates, latency, and cost efficiency.

Implement observability layers that track agent decisions, tool usage, retrieval effectiveness, and drift across models and prompts.

Drive optimization strategies for token efficiency, caching, batching, and inference scaling.

Ensure compliance with Responsible AI principles, enterprise governance standards, audit requirements, and regulatory constraints.

Partner with enterprise architecture, cybersecurity, and data governance teams to define secure deployment patterns.

Mentor engineers on LLM orchestration patterns, workflow decomposition, and safe agent design.

Translate executive-level business objectives into scalable AI platform capabilities.

Lead proof-of-concepts through full production deployment with measurable ROI outcomes.

Continuously evaluate emerging foundation models, orchestration frameworks, and agent tooling for enterprise readiness.

Qualifications

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or related discipline.

7-10+ years of experience in AI engineering, machine learning systems, or distributed software architecture.

3-5+ years designing and deploying LLM-powered systems in production environments.

Demonstrated experience architecting full agentic AI systems with planning, reflection, memory, and tool execution components.

Deep expertise in RAG architectures, embedding strategies, vector databases, and retrieval optimization.

Strong experience designing multi-agent orchestration frameworks and workflow engines.

Advanced proficiency in Python and enterprise API integration patterns.

Experience building secure, scalable microservices in cloud-native environments.

Strong understanding of distributed systems, event-driven architectures, and system reliability principles.

Experience implementing structured output enforcement, guardrails, and audit logging mechanisms.

Demonstrated ability to design evaluation and benchmarking frameworks for LLM and agent reliability.

Experience operating in regulated industries such as insurance, financial services, or healthcare preferred.

Proven leadership in technical design reviews, architecture governance, and cross-functional collaboration.

Strong ability to balance innovation with enterprise risk management and operational stability.

Sedgwickis an Equal Opportunity Employer and a Drug-Free Workplace.

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.

What Sedgwick employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply