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Claude Jobs in Colorado (NOW HIRING)

LLM integration with Anthropic Claude (primary), with multi-model routing where it makes sense. * Evaluation pipelines: how we measure response quality, regression-test prompts, and ship LLM ...

We build with and alongside AI--including Claude--and we are looking for a PM who shares that mindset. We want someone who sees AI as a lever for better member experiences and team efficiency, not ...

Product Manager, Mobile

Denver, CO · On-site

$100K - $110K/yr

We build with and alongside AI-including Claude-and we are looking for a PM who shares that mindset. We want someone who sees AI as a lever for better member experiences and team efficiency, not just ...

Design, build, and deploy internal AI-enabled solutions using enterprise platforms such as Claude Code, Glean, retrieval-based systems, agentic workflows, and orchestration frameworks. * Create ...

Our Engineering team is AI-forward by culture and conviction--we build with AI and use AI to build, including Claude as a core part of our workflow. We expect our TPM to lead from the front on both.

Showing results 41-60

Claude information

What is a Claude?

Claude jobs typically refer to roles related to working with Claude, an artificial intelligence chatbot developed by Anthropic. These jobs can include positions such as AI prompt engineers, machine learning researchers, data scientists, product managers, and customer support specialists who focus on optimizing and deploying Claude for users. Individuals in these roles may work on improving the chatbot's capabilities, ensuring ethical AI use, and supporting its integration across various platforms. The demand for Claude-related jobs has grown as businesses seek to leverage advanced conversational AI solutions.

What skills and qualifications are needed to thrive as a Claude AI engineer?

To thrive as a Claude AI Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree or equivalent experience. Familiarity with programming languages such as Python, deep learning frameworks like TensorFlow or PyTorch, and cloud computing platforms is typically required. Creative problem-solving, collaboration, and effective communication are essential soft skills for working with cross-functional teams and translating complex research into practical solutions. These skills and qualities are crucial for developing, optimizing, and deploying advanced AI systems that meet real-world needs.

How does a machine learning engineer typically collaborate with data scientists and software developers on AI projects?

Machine Learning Engineers often work closely with data scientists to translate experimental models into scalable, production-ready solutions. While data scientists focus on data exploration and developing prototypes, ML Engineers are responsible for optimizing code, implementing robust data pipelines, and ensuring models can be deployed efficiently. Collaboration with software developers is also essential to integrate machine learning models into broader applications, ensuring seamless user experiences and system reliability. Regular cross-functional meetings and agile workflows help align project goals and address challenges collaboratively.

What is the difference between Claude vs Chatbot Developer?

AspectClaudeChatbot Developer
Required CredentialsAI/ML certifications, programming skillsProgramming, AI, UX/UI design
Work EnvironmentAI research labs, tech companiesSoftware companies, startups
Industry UsageAI language models, NLP projectsCustomer service bots, conversational apps

Claude and Chatbot Developer roles both involve AI and programming skills, but Claude typically refers to AI language models or systems, while Chatbot Developers focus on creating conversational interfaces. Claude professionals work more on AI model development, whereas Chatbot Developers design and implement user-facing chatbots. Both roles are essential in AI and tech industries, but their focus areas differ based on the project scope and end-user interaction.

What are popular job titles related to Claude jobs in Colorado?

For Claude jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Claude jobs?

Cities in Colorado with the most Claude job openings:

Infographic showing various Claude job openings in Colorado as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, and 5% Contract. Highlights an 73% Physical, 6% Hybrid, and 21% Remote job distribution.

Senior Full Stack AI Engineer

Ombud

Denver, CO • Hybrid

Full-time

Re-posted 19 hours ago


Job description

  • Location: Denver, CO (hybrid — Tue/Wed/Thu in office)
  • Reports to: CEO
The role

We're hiring a senior full-stack engineer to build the next generation of Ombud's agentic AI platform. The work splits across two domains: building the agentic engine itself (LlamaIndex / agent orchestration / tool calling / evaluation pipelines) and the ML data engineering that supports it (embeddings, vector store operations, retrieval quality, RAG/CAG architectures).

These are high-output IC roles. You will ship production code, own systems end-to-end, and operate without a layer of engineering management between you and the product direction. You will work directly with the CEO on architectural decisions and directly with the platform engineer on production deployment. We are not hiring engineering managers and we are not hiring junior engineers.

What you'll own
  • Ombuddy Native: our next-generation agentic platform replacing the existing Chrome extension. Production agent orchestration, tool design, multi-step reasoning workflows.
  • RAG and CAG architecture: embeddings, retrieval, re-ranking, caching strategies. We use LlamaIndex and Qdrant today; we will evolve the stack as needed.
  • LLM integration with Anthropic Claude (primary), with multi-model routing where it makes sense.
  • Evaluation pipelines: how we measure response quality, regression-test prompts, and ship LLM-dependent features with confidence.
  • Self-service infrastructure: customer onboarding flows, content ingestion automation, in-product setup experiences.
  • Full-stack feature delivery across Python (primary backend), Node.js (legacy services), React (frontend), PostgreSQL, and Elasticsearch.
  • Production operations: own your features through deployment, monitoring, and customer-facing incidents.
  • Code review and technical mentorship within a small, senior engineering team.
Must-haves
  • 6+ years of professional full-stack software engineering experience, with demonstrated production system ownership.
  • Deep Python fluency. JavaScript / TypeScript / React competence.
  • Hands-on production experience integrating LLMs into product (Anthropic, OpenAI, Google) — not academic, not prototype work, but features that customers use.
  • Working knowledge of RAG architectures, embeddings, vector databases, and the trade-offs between retrieval and context-caching approaches.
  • Fluency with Claude Code or similar AI-augmented development workflows. We expect our engineers to use AI as a force multiplier on their own output.
  • Strong intuition for system design: can take a vague product goal, design the architecture, and ship the implementation without needing intermediate hand-holding.
  • Comfort operating in a small team without a layer of engineering management. You bring problems with proposed solutions, not just problems.
  • Willingness to be in-office Tuesday through Thursday in Denver.
Nice-to-haves
  • Production experience with LlamaIndex, LangChain, LangGraph, or similar agent orchestration frameworks.
  • Experience designing and operating evaluation pipelines for LLM applications (Langfuse, Braintrust, or custom).
  • Vector database operations at scale (Qdrant, Pinecone, Weaviate).
  • Browser extension or Office add-in development (Chrome extensions, Office365 / Excel add-ins).
  • Open source contributions, particularly in the AI tooling ecosystem.
  • Prior experience in revenue operations, sales enablement, or response management software.
What success looks likeFirst 30 days
  • Ship your first production pull request within the first two weeks.
  • Develop a working mental model of the codebase across the agentic engine, frontend, and platform layers.
  • Take ownership of one feature in flight.
First 60 days
  • Own a feature end-to-end: design, implementation, deployment, observability.
  • Contribute meaningfully to an architectural decision (engine choice, retrieval strategy, eval design).
  • Be on-call rotation capable.
First 90 days
  • Drive a substantive piece of the Ombuddy Native or self-service roadmap.
  • Establish yourself as a trusted technical voice on architectural decisions.
  • Ship measurable improvements to either response quality, system performance, or developer velocity.
Why Ombud

This is the engineering team that builds the actual product behind the agentic enterprise era. We use Claude as a teammate, not a feature checkbox. We deploy frequently, ship real customer value, and trust our engineers to operate as senior partners — not as cogs in a sprint. If you've been waiting for an environment where your AI fluency translates directly to product impact, this is it.

ABOUT OMBUD

Ombud is a Denver-based B2B SaaS company building the agentic AI platform that powers Revenue Operations teams at enterprises like Workday, UKG, and Prudential. Our product, Ombuddy, automates the response work — RFPs, security questionnaires, proposals — that has historically eaten enterprise sales cycles. Our 2026 strategy is to extend this from response management into Orchestrated Revenue Operations: autonomous execution of the discrete sales processes that move revenue. Our 2035 BHAG is $1B ARR powering 80% of discrete B2B sales motions.

We run on EOS. We hire for output, not pedigree. We expect honesty over politeness, decisions over discussions, and execution over enthusiasm.

HOW WE WORK — PIRCC VALUES
  • Progressive — We grow. We learn. We push the model forward, not protect the status quo.
  • Integrity — We do the right thing and keep our commitments. Said and done are the same thing.
  • Resourceful — We turn constraints into creativity. We do more with less and bring solutions, not problems.
  • Customer-Centric — Our customers' success is the metric that matters. We anticipate their needs and earn their trust.
  • Community — We build a team people want to be part of, and we invest in the communities we serve.