Senior AI Technical Lead

Overview

Remote
Depends on Experience
Full Time

Skills

Machine Learning (ML)
Python
Kubernetes
Google Cloud Platform
Artificial Intelligence
Cloud Computing
Cloud Architecture

Job Details

***********************100% Remote*********************

Client has an immediate need for a Senior AI Technical Lead to join their growing AI and Automation practice. In this role, you will design and lead the development of cutting-edge AI solutions that drive real-world impact across federal programs. You will guide cross-functional teams, shape technical strategy, and mentor engineers in a fast-paced, mission-driven environment. The ideal candidate is a hands-on leader with a strong background in AI/ML development, cloud platforms, and enterprise-scale systems design.

Responsibilities include, but are not limited to:

  • Lead the design, development, and deployment of scalable AI and ML models and systems
  • Translate business requirements into technical solutions across multiple federal missions
  • Oversee the AI/ML development lifecycle, including architecture design, experimentation, and performance optimization
  • Collaborate with cross-functional teams (DevOps, Data Engineering, Cybersecurity) to integrate AI into production environments
  • Provide technical mentorship and conduct code/design reviews for junior and mid-level engineers
  • Research and evaluate emerging AI/ML tools, technologies, and frameworks to drive innovation
  • Ensure all solutions meet federal security, compliance, and cloud architecture standards

Qualifications

  • Master s degree in AI, Machine Learning, or a related field
  • Minimum of 5+ years of hands-on experience in AI/ML solution development
  • Demonstrated experience leading AI/ML initiatives or technical teams
  • Strong understanding of agentic AI including Transformers, Model Context Protocol, Agent2Agent Protocol, LangGraph, and other modern frameworks.
  • Proficiency in Python and Typescript for application development and advanced scripting,
  • Experience deploying AI solutions in AWS, Azure, or Google Cloud Platform environments
  • Familiarity withCI/CD, containerization (Docker, Kubernetes), and DevOps principles
  • Experience with Agile methodologies and tools (e.g., Git, Jira)
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