Agentic AI Engineer

Liberty Blume; Denver (CO); Hybrid; USD 95,000 - 135,000; Full time

Job summary

Liberty Blume in Denver is seeking an Agentic AI Engineer for a hybrid role. You will design and deploy multi-agent systems, orchestrate complex RAG pipelines, and deliver production-ready agentic solutions that automate processes across teams.

The role emphasizes hands-on delivery with immediate impact, strong Python engineering, and experience with cloud platforms. Collaboration with engineering and business units is key to success.

Qualifications

• Proven production experience building agentic AI systems.
• Strong Python engineering skills with clean, tested code.
• Hands-on experience designing RAG pipelines (chunking, embeddings, retrieval).
• Experience working with vector databases in production.
• Familiarity with agent frameworks (LangChain, LangGraph, CrewAI, AutoGen).

Responsibilities

• Design and build multi-agent systems for autonomous reasoning and task execution.
• Architect orchestration patterns including tool use and memory management.
• Deliver solutions across knowledge retrieval and process automation use cases.
• Develop end-to-end RAG architectures (ingestion, embedding, retrieval).
• Monitor and optimise agents for cost, latency, and production readiness.

Skills

Python

RAG pipelines

LLM evaluation

Agent frameworks

LangChain

Cloud platforms

Performance optimization

Knowledge graphs

Tools

LangGraph

CrewAI

AutoGen

Neo4j

Vertex AI

Job description

We’re looking for an Agentic AI Engineer to join our team in Denver. This hybrid role offers flexibility, with two days in the office and three days working remotely.

Opening Date: 14/08/2026

End Date: 11/09/2026

This role sits within a newly established AI engineering squad, working across the full agentic stack. You’ll design agent architectures and RAG pipelines and deliver autonomous agents into production to replace manual processes. It’s a hands-on, delivery-focused role with immediate impact from day one.

Agentic AI engineering is a rapidly evolving field, so we don’t expect years of experience in a discipline that’s still emerging. What matters is a track record of building real, production-grade solutions, strong software engineering fundamentals, and the curiosity to stay ahead. If you’ve been working in this space for 18+ months and can demonstrate live systems you’ve built, we’d love to hear from you.

What will you be doing?

• Design and build multi-agent systems for autonomous reasoning, planning, and task execution
• Architect orchestration patterns including tool use, memory, reflection loops, and human-in-the-loop handoffs
• Deliver solutions across use cases such as developer productivity, knowledge retrieval, and process automation
• Leverage GCP-native and enterprise-grade managed services ahead of building custom infrastructure
• Develop end-to-end RAG architectures (ingestion, chunking, embedding, retrieval, reranking)
• Select and manage appropriate vector databases and build pipelines to turn unstructured data into usable insights
• Apply knowledge graph approaches (e.g. Neo4j) where deeper relational or semantic reasoning is needed
• Define and implement evaluation frameworks, including automated testing and LLM-based assessment
• Monitor and optimise agents for cost, latency, quality, and production performance
• Collaborate across engineering and business teams to build scalable, compliant (GDPR/EU AI Act) and production-ready agentic solutions

Essential

• Proven experience building and deploying agentic AI systems in production (not just prototypes)
• Strong Python engineering skills, with a focus on clean, tested, maintainable code
• Hands-on experience designing RAG pipelines (chunking, embeddings, retrieval, evaluation)
• Experience working with at least one vector database in a production setting
• Practical experience with LLM evaluation techniques (e.g. automated evals, LLM-as-a-Judge, or similar)
• Familiarity with agent frameworks (e.g. LangChain, LangGraph, CrewAI, AutoGen), with good judgement on when to use them
• Solid understanding of LLM fundamentals, including prompting, tool use, structured outputs, and context management
• Experience working with cloud platforms (GCP preferred; AWS or Azure also considered)

Desirable

• Experience with Google Agent Development Kit (ADK) or Vertex AI Agent Builder
• Understanding of MCP (Model Context Protocol) and agent-to-agent communication patterns
• Experience with knowledge graphs or graph databases (e.g. Neo4j, JanusGraph)
• Familiarity with LLMOps and observability tools (e.g. LangSmith, Langfuse)
• Experience building solutions in regulated or enterprise environments
• Background in BPO, AP automation, or document processing workflows

What’s in it for you?

We offer a competitive salary, bonus & benefits

The base salary range is $95,000 - $135,000 based on the level of experience

A Few Benefits Our Employees Enjoy

• Comprehensive benefit plans (medical/dental/vision) starting on day 1
• 401(k) with 100% match up to 10% of base salary in the form of Company Stock (LBTYK series)
• Discretionary Bonus Incentive (annually)
• Discretionary Equity Grants (annually)
• Paid time off
• Access to a private café, fitness centre, and paid parking
• Liberty Global participates in the E-Verify program

Who We Are

Liberty Blume, a Liberty Global company, is a rapidly growing business services provider, specialising in tech-enabled back-office solutions. Our mission is to deliver efficiency, scale and value to our customers through Business, Procurement and Financial Solutions. If you’re curious, customer centric and enjoy being one step ahead, join us on our scale up journey and unlock your freedom to grow!

Liberty Global is an equal opportunity employer, committed to an inclusive environment and accommodating all candidates. We’re eager to hear from you, no matter your background.