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Remote Retrieval Augmented Generation Jobs in Pittsburgh, PA

Understanding of retrieval-augmented generation (RAG) techniques. * Background in MLOps practices ... We are fully remote, with team members in the United States and Europe. Benefits include: * Equity ...

Generative AI (LLMs, prompt engineering, retrieval-augmented generation) * Cloud-native AI platforms (Azure ML, AWS SageMaker, GCP Vertex AI) * Distributed data systems (Spark, Databricks)

Sr. Python Developer/Team Lead

Pittsburgh, PA · On-site +1

$135K - $167K/yr

Can be Remote within a 2 hour drive; Office located in Downtown Pittsburgh (free parking) Job Type ... This individual will lead the development of next-generation applications that combine robust ...

Remote Retrieval Augmented Generation information

What is remote retrieval augmented generation?

Remote Retrieval Augmented Generation (RAG) is an advanced AI technique that combines large language models with external information sources. In a remote RAG setup, the model retrieves relevant data from remote databases or APIs during the generation process, enhancing its responses with up-to-date or domain-specific knowledge. This approach is widely used in applications that require accurate, context-aware answers, such as chatbots, search engines, and virtual assistants. By leveraging remote retrieval, RAG systems can access a broader range of information without needing to store all data locally.

What skills and qualifications are needed to thrive as a remote retrieval augmented generation engineer?

To thrive as a Remote Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, often backed by a degree in computer science or a related field. Familiarity with tools and frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and experience with retrieval systems such as Elasticsearch or FAISS are typically required. Problem-solving, effective communication, and adaptability are important soft skills for collaborating remotely and iterating on rapidly evolving AI solutions. These skills ensure the engineer can design, deploy, and optimize robust RAG systems that effectively combine retrieval and generation for high-quality AI outputs.

What are common challenges faced by professionals working in remote retrieval augmented generation roles, and how can they be addressed?

Professionals in Remote Retrieval Augmented Generation (RAG) roles often encounter challenges related to integrating diverse data sources, ensuring low latency in information retrieval, and maintaining the quality and relevance of augmented outputs. Coordinating effectively with distributed teams and adapting to rapidly evolving AI technologies are also common hurdles. To address these, staying current with best practices in data engineering, leveraging robust APIs, and participating in regular team check-ins can help ensure smooth collaboration and system performance.

What is the difference between Remote Retrieval Augmented Generation vs Remote Data Scientist?

AspectRemote Retrieval Augmented GenerationRemote Data Scientist
CredentialsAI/ML knowledge, programming skillsStatistics, programming, domain expertise
Work EnvironmentAI development, NLP projectsData analysis, model building
Industry UsageAI, NLP, machine learningTech, finance, healthcare
Search & ComparisonOften compared for AI roles involving language modelsCompared for data analysis roles

Remote Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, requiring expertise in AI, NLP, and programming. Remote Data Scientists analyze data, build models, and interpret results, often with statistical and domain knowledge. While both roles may work remotely and involve data handling, Retrieval Augmented Generation emphasizes AI model development, whereas Data Scientists focus on data analysis and insights.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Pittsburgh, PA?

The most popular types of Retrieval Augmented Generation jobs in Pittsburgh, PA are:

What are popular job titles related to Remote Retrieval Augmented Generation jobs in Pittsburgh, PA?

For Remote Retrieval Augmented Generation jobs in Pittsburgh, PA, the most frequently searched job titles are:

What job categories do people searching Remote Retrieval Augmented Generation jobs in Pittsburgh, PA look for?

The top searched job categories for Remote Retrieval Augmented Generation jobs in Pittsburgh, PA are:

What cities near Pittsburgh, PA are hiring for Remote Retrieval Augmented Generation jobs?

Cities near Pittsburgh, PA with the most Remote Retrieval Augmented Generation job openings:

AI Engineer

Epistemix

Pittsburgh, PA • Remote

Full-time

Medical, Retirement

Re-posted yesterday


Job description

The AI Engineer plays a critical role in making modeling and simulation accessible to non-data scientists. You will be designing, developing, and deploying AI-driven applications to make our software more accessible which will have a direct impact on the number of organizations we are able to serve. This position plays a critical role in our product roadmap and will directly contribute to the company's success and growth. Ideal candidates exhibit a high willingness to experiment and empathy for users.

About Epistemix

The most consequential decisions in public health, life sciences, insurance, and enterprise strategy share a common problem: they involve human behavior, network effects, and downstream effects that cannot be safely tested before action is taken. Traditional analytical techniques built on historical data were not built for this. Epistemix was.

We build simulation and data-driven modeling tools that let leaders visualize how strategies will unfold across populations and systems before they commit resources. By clarifying which variables drive outcomes, where leverage exists, and how they interact, we help organizations move from uncertainty to conviction. Getting these decisions right means faster interventions, better-allocated resources, and measurable improvements in human and economic outcomes. We exist to make that possible.

Our platform gives organizations access to realistic, high-resolution population data and the modeling infrastructure to run scenario planning at scale. Together, these capabilities let decision-makers stress-test strategies in a controlled environment before deploying them in the real world across healthcare, consumer industries, insurance, and government. We are approaching our Series B and actively building the team that will define what comes next.

Responsibilities
  • Craft clean, testable, and maintainable code to enable AI-generated agent-based models.

  • Own the software from requirements development through deployment and maintenance that enable decision makers to generate agent-based models that address critical business questions and data scientists to build agent-based models more quickly that answer the questions of decision makers.

  • Design, build, test, and deploy a scalable system architecture so that AI-generated models can be validated by data scientists and deliver results back to decision makers quickly.

  • Own the engineering solution and collaborate with internal teams to ensure alignment with company strategy.

Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field (or equivalent experience).

  • 3+ years of experience developing AI/ML applications in production environments.

  • Proven track record of working with LLMs, NLP models, or AI-driven systems.

  • Experience designing and optimizing high-performance, scalable APIs.

  • Strong problem-solving skills and ability to work in a fast-paced environment.

  • Must be legally authorized to work in the United States and not require employer sponsorship now or in the future.

Required Skills
  • Python – Advanced proficiency in writing clean, efficient, and scalable code.

  • Pydantic – Strong experience in data validation, serialization, and structured model definition.

  • LLM Evaluation – Ability to assess model performance, optimize outputs, and fine-tune AI behavior.

  • Prompt Optimization – Expertise in crafting, refining, and iterating prompts for optimal AI performance.

  • SQLAlchemy – Hands-on experience with database modeling, ORM techniques, and performance tuning.

  • FastAPI – Proven ability to develop and maintain APIs with FastAPI for AI-driven applications.

Nice to Have Experience
  • Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) for efficient AI retrieval.

  • Familiarity with Docker & Kubernetes for containerized AI application deployment.

  • Knowledge of cloud platforms (AWS, GCP, or Azure) for scaling AI infrastructure.

  • Understanding of retrieval-augmented generation (RAG) techniques.

  • Background in MLOps practices for automating AI model deployment and monitoring.

Why Join Epistemix?

By joining Epistemix, you will become part of a collaborative and rapidly growing team that values curiosity and creativity. We are fully remote, with team members in the United States and Europe. Benefits include:

  • Equity & Incentives – Participation in our stock option program.

  • Flexible Time Off – Autonomy to manage your schedule and work-life balance.

  • Health, Welfare and 401(k) Programs – Eligibility for benefits (for U.S. employees).

  • Meaningful Impact – Apply your creative talents to revolutionize data-driven decision-making and make a real-world difference.

This is a remote position open to applicants located in the United States. Candidates must possess the legal right to work in their intended work location, as we are currently unable to sponsor or transfer employment visas for any country, including the United States.