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CodeRoad

AI Engineer

CodeRoad

. Develop production-grade AI agents, state management mechanisms, and multi-agent workflows .

Posted 11/1/2026full-timeRemoteMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing AI agents and implementing high-performance RAG pipelines, with a strong focus on Python programming and AWS deployment. Collaborates effectively with cross-functional teams to deliver impactful software solutions while maintaining comprehensive technical documentation.

Highest-signal resume keywords
Advanced PythonAWS DeploymentLLM-Based ApplicationsVector DatabasesModel Context Protocol

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Software DevelopmentAI Agent DevelopmentRAG Pipeline ImplementationAutomated TestingRegression TestingPerformance OptimizationPrompt Injection DefenseTechnical DocumentationAnalytical TroubleshootingCross-Functional Collaboration
Soft Skills
Ownership MindsetCollaborative ApproachAnalytical Thinking
Tools & Technologies
Amazon BedrockLangSmithLangtraceAgentOpsPineconeWeaviateLangGraphCrewAIADK
Industry Keywords
AI ApplicationsMulti-Agent WorkflowsEnterprise Tools IntegrationSemantic SearchChunking StrategiesGrounding Strategies

Tech Stack

Tools & technologies
AWSPython

About the role

Key responsibilities & impact
  • Develop production-grade AI agents, state management mechanisms, and multi-agent workflows
  • Connect AI agents to enterprise tools, APIs, and external platforms via Model Context Protocol and structured function calling
  • Implement and maintain high-performance RAG pipelines using vector databases, semantic search, chunking, and grounding strategies
  • Execute automated evaluations, regression testing, task-success metrics, and safety guardrails
  • Defend against prompt injection and sensitive-data exposure
  • Deploy LLM applications on AWS using Amazon Bedrock
  • Use observability platforms such as LangSmith, Langtrace, or AgentOps to troubleshoot failures and optimize performance
  • Write clean, maintainable, and testable Python code
  • Maintain comprehensive technical documentation
  • Collaborate with senior engineers, MLOps, and product teams

Requirements

What you’ll need
  • 3+ years of professional software development experience
  • Direct, hands-on experience building LLM-based, RAG, or agentic AI applications
  • Mastery of advanced Python
  • Mastery of AWS, including Amazon Bedrock
  • Experience with agentic frameworks such as LangGraph, CrewAI, or ADK
  • Experience with vector databases such as Pinecone or Weaviate
  • Knowledge of Model Context Protocol (MCP)
  • Hands-on experience testing, evaluating, and monitoring LLM execution using LangSmith, Langtrace, or AgentOps
  • Strong ownership mindset and analytical troubleshooting capabilities
  • Advanced English skills, written and spoken, mandatory
  • Collaborative approach to delivering high-impact software within cross-functional teams

Benefits

Comp & perks
  • Agentic AI tools and training
  • Coursera Enterprise
  • Studio practice labs
  • High-touch onboarding
  • Transparent leadership communication
  • Community recognition
  • Psychological safety
  • Holidays off
  • Paid time off
  • Health insurance assistance program
  • Opportunity to work with high-growth US-based companies and cutting-edge tech stacks