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Llm Backend Engineer Jobs in Colorado (NOW HIRING)

Ombud

Senior Full Stack AI Engineer

Denver, CO · On-site

LLM integration with Anthropic Claude (primary), with multi-model routing where it makes sense ... Full-stack feature delivery across Python (primary backend), Node.js (legacy services), React ...

Ombud

Senior Full Stack AI Engineer

Denver, CO · Hybrid

LLM integration with Anthropic Claude (primary), with multi-model routing where it makes sense ... Full-stack feature delivery across Python (primary backend), Node.js (legacy services), React ...

Ombud

Senior Full Stack AI Engineer

Denver, CO · Hybrid

LLM integration with Anthropic Claude (primary), with multi-model routing where it makes sense ... Full-stack feature delivery across Python (primary backend), Node.js (legacy services), React ...

Socket.dev

Senior Engineer - Growth

Denver, CO · On-site

$181.22 - $217.46/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design, build, and own new backend services and APIs end-to-end, from technical proposal through ... Experience with AI/LLM technologies, recommendation systems, data science, or data modeling.

Litera

Senior Software Engineer

Denver, CO · On-site

$130K - $175K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

NET backend, TypeScript/React frontend, and cloud-based services. * Design scalable APIs, services ... Experience building AI-powered products, LLM-based workflows, RAG systems, agents, or integrations ...

Ibotta

Senior Data Engineer

Denver, CO · On-site

$109K - $148K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

You'll grow into LLM application development and semantic layer work as the team evolves. This ... or backend development. * Project Leadership: Demonstrated ability to lead complex, multi ...

S27a

Senior Software Engineer Hybrid (Denver, CO)

Denver, CO · On-site

$127.50 - $172.50/hr

  • Medical

  • Dental

  • Vision

Strong backend proficiency, building APIs / middleware / web frameworks.* Solid SQL and relational ... Prior work with LLM APIs or AI workflow design.## What We Offer* Base salary: $150,000* Great ...

Havenly

Staff Software Engineer, Design Services

Denver, CO · On-site

$185K - $220K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Alongside our agent platform and LLM tooling, we're building an internal harness so agents can take ... Backend: PHP, Node/TypeScript, a TypeScript GraphQL layer, Python. * 3D and Studio: Python ...

Jobtailor

Senior Software Engineer - Mobile

Denver, CO · On-site

$120 - $180/hr

Track record of mentoring more junior engineers and improving the technical quality of the team ... backend stack: PHP, MySQL, AWS. * Experience with agentic AI workflows or building LLM-powered ...

Socket.dev

Senior Software Engineering Manager

Denver, CO · On-site

$180 - $200/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Lead, mentor, and grow a team of full-stack, frontend and backend engineers across a few squads ... Evaluate and implement LLM integrations and emerging AI technologies into the product interface to ...

Apex Systems

AI Software Engineer

Englewood, CO · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

... backend services using Java Spring Boot for integration, APIs, and enterprise workflows Create ... LLM models for reasoning, generation, and decision-making capabilities Manage and optimize vector ...

New

Focused

Agent Engineer (Langchain)

Denver, CO · On-site

$120K - $175K/yr

Lead teams through end-to-end delivery across the stack, from backend services to modern web UIs ... Helped design an architecture that integrates LLM agents into a legacy enterprise workflow

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All JobsLlm Backend Engineer JobsLlm Backend Engineer Jobs in Colorado

Llm Backend Engineer information

What are some common challenges faced by LLM backend engineers when deploying large language models in production?

LLM Backend Engineers often encounter challenges such as optimizing inference latency, managing high resource consumption, and ensuring scalability for production workloads. Balancing model performance with cost efficiency requires careful selection of hardware, batching strategies, and model quantization techniques. Additionally, they must address security and privacy concerns associated with handling sensitive data processed by the models. Collaboration with data scientists and DevOps teams is essential to streamline model updates and monitor system health.

What is an LLM backend engineer?

LLM Backend Engineers are software engineers who specialize in designing, building, and optimizing the backend infrastructure that supports large language models (LLMs) like GPT-4. They focus on integrating LLMs into products and services, ensuring scalable APIs, managing data pipelines, and optimizing inference performance. Their work often involves deploying models in cloud environments, monitoring system reliability, and collaborating with AI researchers to bring advancements into production. LLM Backend Engineers play a critical role in making AI-powered applications robust, efficient, and accessible to end users.

What are the key skills and qualifications needed to thrive as an LLM backend engineer?

To thrive as an LLM Backend Engineer, you need a solid foundation in software engineering, backend architecture, and experience working with large language models, typically supported by a degree in computer science or a related field. Proficiency with programming languages like Python or Java, cloud platforms (AWS, GCP, Azure), and machine learning frameworks such as TensorFlow or PyTorch is essential, along with familiarity with APIs and containerization tools like Docker or Kubernetes. Strong problem-solving, collaboration, and communication skills distinguish top performers in this role. These skills ensure robust, scalable, and efficient deployment of LLM-powered applications while enabling effective teamwork and innovation.

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Llm Backend Engineer jobs near you

Senior Full Stack AI Engineer

Ombud

Denver, CO • On-site

Full-time

Re-posted 10 days 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 like
First 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.

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