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Python Llm Jobs in Park City, UT (NOW HIRING)

OC Tanner

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

Python / FastAPI microservices * LangChain / LangGraph * GraphQL / REST * PostgreSQL / Redis ... Designed LLM strategies covering tool calling, structured outputs, prompt engineering, and context ...

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Senior GTM Engineer

Lehi, UT · On-site

$150 - $210/hr

This role suits a builder-leader who's equally comfortable writing SQL and Python as they are ... You've built or evaluated agentic frameworks and applied LLM evaluation at scale. * You have ...

Brex

Systems Analyst II

Salt Lake City, UT · Hybrid

$126K - $145K/yr

Integrate AI and LLM-based capabilities into existing tools and workflows to drive automation and ... Working proficiency in JavaScript, Python, SQL, and APIs, with the ability to build and ship ...

Weave

Senior GTM Engineer

Lehi, UT · On-site

$98K - $134K/yr

This role suits a builder-leader who's equally comfortable writing SQL and Python as they are ... You've built or evaluated agentic frameworks and applied LLM evaluation at scale. * You have ...

Addepar

Portfolio Analytics Architect

Salt Lake City, UT · On-site

$103K - $129K/yr

Write custom Python logic to detect large-scale data anomalies and automate remediation ... Identify and implement AI-driven automation and LLM integrations to streamline implementation Who ...

Podium

Senior AI Engineer - Agentic

Lehi, UT · On-site +1

$98K - $134K/yr

... Python, or Elixir. * 1+ years of professional experience deploying and maintaining AI agents in ... Practical experience designing and implementing evaluations for LLM behavior - including accuracy ...

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Python Llm information

See Park City, UT salary details

$13

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How much do python llm jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for python llm in Park City, UT is $61.33, according to ZipRecruiter salary data. Most workers in this role earn between $50.53 and $69.66 per hour, depending on experience, location, and employer.

What is a Python LLM?

A Python LLM job involves working with Large Language Models (LLMs) using Python to develop, fine-tune, and deploy AI models. Responsibilities may include data preprocessing, prompt engineering, model optimization, and integration with applications. Professionals in this role often work with frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. They may also contribute to improving model efficiency, reducing bias, and ensuring ethical AI usage.

What are the key skills and qualifications needed to thrive in the Python LLM position, and why are they important?

To excel as a Python LLM (Large Language Model) Engineer, you need strong skills in Python programming, machine learning, and natural language processing, typically supported by a degree in computer science or a related field. Proficiency with libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and experience with model deployment platforms are often essential, alongside certifications in AI or data science. Effective communication, problem-solving abilities, and collaboration are important soft skills for working in interdisciplinary teams and delivering results in dynamic environments. These skills ensure the development, fine-tuning, and deployment of advanced language models that meet both technical and business objectives.

What are some common challenges faced by Python LLM engineers in their daily work?

Python LLM Engineers often encounter challenges related to optimizing model performance, managing large datasets, and adapting models to specific business needs. Working with large-scale language models requires balancing computational resource limitations with the need for high accuracy and efficiency. Collaboration with data scientists, product managers, and DevOps engineers is routine to ensure seamless model integration and deployment. Staying updated on the latest advancements in NLP and continuously improving models based on user feedback are also important aspects of the role.

What cities near Park City, UT are hiring for Python Llm jobs?

Cities near Park City, UT with the most Python Llm job openings:

Python Llm jobs near you
Infographic showing various Python Llm job openings in Park City, UT as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 75% Physical, 6% Hybrid, and 19% Remote job distribution, with an average salary of $127,558 per year, or $61.3 per hour.

Sr. Applied AI Engineer

OC Tanner

Salt Lake City, UT • On-site

$101K - $138K/yr

Full-time

Re-posted 21 days ago

Job description

O.C. Tanner is the global leader in software and services that improve workplace culture through meaningful employee experiences. Our Culture Cloud is a suite of apps designed to enhance the employee experience with strategic recognition, service awards, wellbeing, leadership, and events that help people thrive at work. Our Culture by Design approach provides expert services to organizations looking to create great workplaces.
Our global team of 1,500 people hail from 58 countries and speak 62 languages. As programmers, researchers, designers, client professionals and craftspeople we create the tech, tools and awards that connect employees to purpose at thousands of companies. Join us as we help people all over the world thrive at work.
About the Role
AI is becoming part of the product and platform architecture we need to build, operate, and scale. We are looking for an Applied AI Engineer who can turn AI capability into secure, measurable, governed production systems, not prototypes or demos. This person will help define how O.C. Tanner builds agentic systems that pursue goals, use tools, follow guardrails, recover from failure, and deliver real value inside user workflows.
This role sits at the intersection of software engineering, product experience, AI platform engineering, and responsible AI. You will partner with Product, UX, Design, Architecture, Security, and Engineering to build AI experiences that are useful, understandable, reliable, and safe to operate in production. The right person has hands-on experience building agentic systems with orchestration, tool calling, memory or state, RAG, evaluation, observability, and human-in-the-loop controls.
Responsibilities
  • Design, build, deploy, and support production-grade agentic AI systems that operate against explicit goals, constraints, policies, and guardrails.
  • Build agent orchestration patterns for multi-step workflows, tool calling, MCP servers, state management, memory, retries, recovery paths, and human-in-the-loop controls.
  • Partner closely with Product, UX, Design, Architecture, Security, and Engineering teams to create AI experiences that are useful, understandable, reliable, and aligned with real user workflows.
  • Design user-centered AI interactions, including conversational flows, feedback loops, confidence handling, explainability, graceful failure modes, escalation paths, and clear boundaries for autonomous behavior.
  • Develop and operate RAG systems that ground model behavior in enterprise knowledge, including ingestion, chunking, embeddings, vector and hybrid retrieval, reranking, retrieval evaluation, and citation or traceability strategies.
  • Define and implement evaluation frameworks for AI systems, including offline test sets, regression suites, adversarial testing, groundedness and faithfulness scoring, task completion metrics, and production quality monitoring.
  • Instrument agentic systems for observability, including traces of model calls, prompts, tool usage, decisions, retrieved context, latency, cost, errors, and user feedback.
  • Establish safeguards for responsible AI use, including prompt injection defense, data access controls, PII protection, bias and toxicity detection, misuse prevention, audit logging, and policy enforcement.
  • Optimize model selection, prompts, context windows, caching, routing, inference patterns, latency, throughput, reliability, and cost across production workloads.
  • Mentor engineers on applied AI practices, including prompt and context engineering, agent design, RAG, evaluation, safety, observability, and production support.
  • Stay current with emerging AI platforms, frameworks, models, and standards.

Our stack
  • Python / FastAPI microservices
  • LangChain / LangGraph
  • GraphQL / REST
  • PostgreSQL / Redis
  • Kafka
  • Kubernetes
  • AWS Bedrock
  • OpenTelemetry
  • Terraform

Qualifications
Required Qualifications
  • 5+ years of software engineering experience with strong Python proficiency
  • 2+ years building production ML or agentic AI systems
  • 1+ years hands-on experience with agentic frameworks (LangGraph, CrewAI, AutoGen, or equivalent)
  • Built production AI systems including agents, MCP servers, multi-step reasoning, and multi-turn conversation
  • Deployed RAG systems including embedding models, vector databases, hybrid search, and retrieval optimization
  • Designed LLM strategies covering tool calling, structured outputs, prompt engineering, and context window management
  • Implemented AI safety and evaluation pipelines covering bias detection, PII leakage, faithfulness scoring, toxicity, and prompt injection mitigation
  • Optimized models for inference efficiency, latency, and cost management

Strongly Preferred
  • Bachelor's degree in Computer Science, Machine Learning, or a related field
  • AWS Certified Machine Learning Engineer - Associate or equivalent
  • Cloud AI infrastructure management using AWS services and Terraform
  • AI observability experience with OpenTelemetry, Langfuse, or equivalent

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