Role overview

Agentic AI Engineer

Requirements and responsibilities

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US Citizenship Required:

  • Architect and implement production-grade multi-agent AI solutions with modern orchestration frameworks, enabling reliable, transparent, and secure agentic workflows
  • Build and maintain end-to-end agentic AI pipelines, from data ingestion and embedding to deployment and continuous evaluation, optimized for reusability and scalability
  • Develop, test, and deploy internal AI applications that enhances people-powered, AI-enabled productivity
  • Provide unified observability with logging, metrics, and alerts and analyze agent runtime behavior to tune latency, accuracy, and cost in production
  • Integrate agentic AI services with existing enterprise systems and uphold AIOps practices for consistent deployment and scaling
  • Collaborate with cross-functional teams including data scientists, software engineers, and product / service owners to align AI projects with business goals
  • Must stay updated on emerging AI related technologies and recommend improvements to existing AI systems

US Citizenship Required:

  • Education: Bachelor’s Degree in Computer Science, Computer Engineering, Data Science or a related field
  • Experience:
  • 5+ years of experience in AI and machine learning, including hands-on experience with designing, developing, and deploying AI models and systems.
  • 1+ years of experience developing products or functional prototypes using RAG and agentic AI technologies.
  • Must have designed and/or implemented hands-on an agentic workflow solution (not just simply prompt engineering to LLMs)
  • Role requirements:
  • Proven track record of delivering end-to-end AI projects and successfully integrating AI solutions into business processes.
  • Proficiency in programming languages such as Python, R, or Java, and deep understanding of machine learning frameworks like TensorFlow or PyTorch.
  • Strong hands-on experience with MCP, LangGraph, LlamaIndex, or similar agentic frameworks.
  • Deep understanding of prompt or context engineering, tool definition, and state management for agents.
  • Experience with cloud computing platforms, such as Azure (Preferred), OCI, AWS, or Google Cloud, including AI services like Azure AI Foundry, Bedrock, or Vertex AI.
  • Strong background in working with large datasets and performing data preprocessing, feature engineering, and model evaluation.
  • Preferred Skills and Abilities: Masters degree. Advanced coursework or a Certification in AI, Machine Learning or related areas desirable
  • Location: Remote
  • US Persons required

US Citizenship Required:

  • Growth: AI-powered career tool that identifies career steps and learning opportunities
  • Support: An internal mobility team focused on helping you achieve your career goals
  • Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
  • Flexibility: Full-flex work week to own your priorities at work and at home
  • Community: Award-winning culture of innovation and a military-friendly workplace
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Browse stack
FocusAI EngineeringRole area
Seniority signalSeniorCandidate level
StackAWS, Azure, JavaPrimary skills
Location1 accepted countryEligibility

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