AI Engineer

Insight Global

Maryland

On-site

USD 140,000 - 190,000

Full time

12 hours ago
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Job summary

Insight Global is seeking an Agentic AI Engineer to join a growing multi-agent AI team responsible for building and deploying autonomous AI agents in production environments. You will design agent architectures, workflows, decision-making systems, and tool integrations to enable autonomous capabilities.

The role requires strong software engineering fundamentals, Python expertise, and experience with AI-enabled products.

Qualifications

  • Active TS/SCI with ability to obtain CI Poly.
  • 5+ years of software engineering experience.
  • Strong Python development experience.
  • Experience building AI agents, agentic workflows, or multi-step LLM systems.
  • Experience integrating APIs, tools, and external services.
  • Experience with agent memory systems, vector databases, or retrieval systems.
  • Understanding of distributed systems and software architecture.
  • Experience with CI/CD pipelines and containerized environments.
  • Bachelor's Degree in Computer Science, Engineering, Data Science, or related field.

Responsibilities

  • Identify mission challenges and translate them into AI/ML solutions and measurable objectives.
  • Gather, analyze, and prepare structured and unstructured datasets for model development.
  • Design feature engineering approaches and data preparation strategies to improve model performance.
  • Develop, train, test, and optimize machine learning and generative AI models.
  • Build and evaluate AI solutions using modern modeling, prompting, and fine-tuning techniques.
  • Establish validation frameworks and performance metrics to measure model effectiveness and reliability.
  • Collaborate with software, data, and platform engineering teams to deploy solutions into operational environments.
  • Monitor models in production, identify performance issues, and implement improvements as needed.
  • Document methodologies, findings, and technical approaches to support transparency and repeatability.
  • Participate in customer engagements, testing activities, troubleshooting efforts, and continuous model enhancement initiatives.
  • Ensure AI solutions align with security, compliance, and mission requirements throughout development and deployment.

Skills

Python development
AI agents / multi-agent systems
APIs & integration
CI/CD pipelines
Distributed systems
Model training / ML
Software engineering fundamentals
Agent memory systems / vector DBs
Containerization (Docker)
Orchestration frameworks (LangGraph/C岑

Education

Bachelor's Degree in Computer Science, Engineering, Data Science, or related field
Master's Degree or PhD in Technical discipline

Tools

Kubernetes
Docker
Redis
PostgreSQL
Vector databases
LangGraph
CrewAI
AutoGen
AWS Bedrock / Foundry / Gemini

Job description

*** Must have an active TS/SCI with ability to obtain CI Poly ***
About the Company

Insight Global is seeking an Agentic AI Engineer to support a growing multi-agent AI team focused on building and deploying AI agents in production environments. This individual will help design and develop agent architectures, workflows, decision-making systems, and tool integrations that enable autonomous AI capabilities. The ideal candidate combines strong software engineering fundamentals with experience building AI-enabled products and can thrive in a highly collaborative environment focused on innovation and ownership.

About the Role

The Agentic AI Engineer will support a growing multi-agent AI team focused on building and deploying AI agents in production environments, designing and developing agent architectures, workflows, decision-making systems, and tool integrations that enable autonomous AI capabilities.

Responsibilities
  • Identify mission challenges and translate them into AI/ML solutions and measurable objectives
  • Gather, analyze, and prepare structured and unstructured datasets for model development
  • Design feature engineering approaches and data preparation strategies to improve model performance
  • Develop, train, test, and optimize machine learning and generative AI models
  • Build and evaluate AI solutions using modern modeling, prompting, and fine-tuning techniques
  • Establish validation frameworks and performance metrics to measure model effectiveness and reliability
  • Collaborate with software, data, and platform engineering teams to deploy solutions into operational environments
  • Monitor models in production, identify performance issues, and implement improvements as needed
  • Document methodologies, findings, and technical approaches to support transparency and repeatability
  • Participate in customer engagements, testing activities, troubleshooting efforts, and continuous model enhancement initiatives
  • Ensure AI solutions align with security, compliance, and mission requirements throughout development and deployment
Required Skills

Active TS/SCI with ability to obtain CI Polygraph 5+ years of software engineering experience Strong Python development experience Experience building AI agents, agentic workflows, or multi-step LLM systems Experience integrating APIs, tools, and external services Experience with agent memory systems, vector databases, or retrieval systems Understanding of distributed systems and software architecture Experience with CI/CD pipelines and containerized environments Bachelor's Degree in Computer Science, Engineering, Data Science, or related field

Preferred Skills

Experience supporting NLP, computer vision, cyber analytics, or advanced AI applications Experience within defense, intelligence, cyber, or national security environments Previous military experience within intelligence, cyber, communications, or technical operations communities Experience working directly with customers or stakeholders to translate operational requirements into technical solutions Master's Degree or PHD in Technical discipline LangGraph, CrewAI, AutoGen, or similar orchestration frameworks Experience designing multi-agent systems Agent memory architecture experience Redis, Postgres, or vector database experience Kubernetes and Docker experience AWS Bedrock, Microsoft Foundry, or Gemini Enterprise experience

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