AI Engineer

Poplicus Incorporated
Pittsburgh, PA, United States
3 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Cloud Computing Computer Engineering Python (Programming Language) Regression Testing Software Tools Systems Integration Data Processing Large Language Models Multi-Agent Systems Backend
+4 more
Git Information Technology Machine Learning Operations Software Version Control

Job description

  • Designs and builds multi-agent systems with tool use, memory, routing, and planning
  • Develops Agent Skills and tools as modular, composable services that interact with backend systems, models, and data processing
  • Own the technical architecture and engineering standards for agentic systems, ensuring scalability, reliability, and maintainability
  • Assist with automated evaluation of agents, skills, and prompts across the entire product lifecycle
  • Work with our Product and Implementation organizations to find solutions to our most vexing challenges, applying agents to our customer problems

Requirements

Do you have experience in Version control?, Do you have a Master’s degree?, * Experience integrating and working with LLMs, with a strong understanding of their capabilities and limitations

  • Experience integrating and working with agent frameworks like Claude Agent SDK or OpenAI Agent SDK
  • Experience building observability, evaluation, and feedback loops for agent behavior (telemetry, prompt evaluation, regression testing, and reliability metrics).
  • Experience working in highly ambiguous environments, and operate with urgency
  • Startup experience, particularly in scaling products from zero to one

Strong Candidates have:

  • Experience designing and deploying complex agentic systems using LLMs
  • Hands-on work with multi-agent coordination, routing, and tool orchestration
  • Love coding agents

This role is a full-time position located out of our office in Pittsburgh, PA., * U.S. Citizenship is required, * Bachelor’s, Master’s, or Doctorate in Computer Science, Computer Engineering, Data Science, or a related field

  • Minimum 1 year of experience building and deploying ML or LLM-powered systems in production environments
  • Practical experience in building, developing, and productionizing machine learning systems
  • Advanced software skills in Python
  • Experience with common LLM algorithms and implementations
  • Hands-on experience with AWS and cloud infrastructure
  • A strong desire to learn and investigate new technologies
  • Familiarity with Git source control management
  • Ability to work collaboratively with little supervision
  • A burning desire to work in a challenging, fast-paced tech environment

Desired Skills:

  • Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
  • Experience in or exposure to the nuances of a startup or other entrepreneurial environment
  • Comfortable with Claude Code and GenAI coding best practices.

We firmly believe that past performance is the best indicator of future performance. If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we’re eager to hear from you.

About the company

Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science & Technology, Production, Sustainment, Logistics, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions., We are seeking an experienced AI Engineer to join our Agentic AI team as we scale our agentic offerings across all levels of the US government. Over the past year, we have seen the rapid adoption of our agent, Ace. We expect Ace to be handling much more complex tasks and workflows end-to-end or in cooperation with a human user as time goes on. The team is striving to make Ace an even more effective agent, focusing on planning, reliable execution over longer time horizon tasks, scaled tool use, Ace Skills, memory, and inter-agent coordination.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

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