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Podium

Staff AI Engineer - Utah

Lehi, Utah; LehiUnited States
Staff · Engineering
POSTED 22 DEC 2025
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Role
321 days opentrue age
Posted 22 Dec 2025
Pay
$230k–$288kno pay posted
Market p25–p75
$230k–$288k
United States · n=295 · 365d to 6 Nov
CompanyPodium →
68open roles
Opened · 30d
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Closed · 30d
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3d of snapshots · 30d window
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1,035open · Staff ML / AI
Opened · 7d
+10110% of open
All ml / ai
6,698open
All tracked boards · live 9 Nov · n=1,035
Visa
1H-1B LCAs · FY25
UK licensed sponsor
✓Worker (A rating)
LCAs FY25 · n=1 · to 2024-10-24
PythonGoLLMsDistributed systems

At Podium, we bring AI Employees to local businesses that turn every conversation into revenue. Trusted by 60,000+ businesses across Auto, Home Services, and Aesthetics, Podium captures and converts leads 24/7, driving both new business and repeat customers.

In 2.5 years, we crossed $150M in AI Agent ARR. During this time, we’ve deployed 10,000 AI employees to empower real business outcomes for our customers. Podium is building what we believe will be the most impactful AI employee ecosystem for local business.

Podium has been recognized as the Best AI Implementation by Inc. Magazine, highlighted by OpenAI for building revenue-driving AI Agents, and awarded the #1 AI Agent for Business Operations by G2.

Our growth is fueled by hiring exceptional people, holding them to high standards, and creating opportunities for them to grow and make an impact. Our operating principles guide daily behavior and ensure we hire people who will thrive at Podium. If you're hungry for growth, aligned to our operating principles, and ready to get to work, you won't find a better place to learn and accelerate your career.

Staff AI Engineer

The Role

We are looking for a talented Staff AI Engineer to help build and scale our AI Agent platform—a powerful system that autonomously interacts with customers, handling millions of conversations every month. In this role, you’ll design and deliver the software that enables local businesses to manage complex customer interactions automatically, book more appointments, and serve their customers more effectively across multiple channels (e.g., voice, SMS, chat).

If you thrive in fast-paced, highly iterative environments, enjoy solving complex distributed systems challenges, and want to see your work drive immediate business impact, this role is for you!

What you will be doing

  • Build and scale the AI Agent platform — enabling high-volume, real-time conversational workflows that deliver accuracy and low latency at scale.
  • Design and implement APIs, services, and infrastructure that power multi-turn, cross-channel customer interactions.
  • Own the full lifecycle: architecture, implementation, deployment, and ongoing reliability.
  • Prototype rapidly, iterate with live interaction data, and continuously improve system performance and user experience.
  • Implement observability, monitoring, and operational best practices to ensure reliability in production, focusing on agent accuracy and latency.
  • Collaborate with engineers, product managers, and AI/ML scientists to deliver end-to-end features that power critical business outcomes.

What you should have

  • 10+ years of professional software engineering experience with at least one modern language such as Go, Python, or Elixir.
  • 1+ years of professional experience deploying and maintaining AI agents in production environments that interact with tools, APIs, or real-world workflows.
  • Proven success designing and maintaining distributed or high-throughput systems.
  • Strong problem-solving ability and comfort navigating ambiguity in large-scale systems.
  • Excellent communication skills and the ability to work effectively across teams.
  • A willingness to work across the entire stack—from infrastructure to APIs to user-facing components—wherever the problem needs solving.
  • Ability to thrive in a fast-paced environment with shifting priorities.
  • Must be willing to work on site, 5 days per week.

What we hope you have

  • 2+ years of professional experience deploying and maintaining AI agents in production environments that interact with tools, APIs, or real-world workflows.
  • Practical experience designing and implementing evaluations for LLM behavior — including accuracy, safety, reliability, and cost monitoring.
  • Strong understanding of prompt design, context engineering, and guardrail strategies for dependable, interpretable agent behavior.
  • Experience with modern agent frameworks such as LangGraph, CrewAI, or AutoGen, including multi-step reasoning, memory, and orchestration patterns.
  • Hands-on experience with fine-tuning and data curation for improving model performance.
Source · PodiumFirst seen 3 Nov1 editsOriginal ↗