• Job Description

  Req#: 25-09598
  AI Developer
  Remote Position
  6+Month Contract
  
  Client is looking for AI Developer with – Python, azure APIM, langraph, langchain, genAI, added adv - azure devops
  
  Key Responsibilities:
  • Curate and ingest internal and vendor documentation, tickets, change requests, and platform-specific knowledge into the AI system.
  • Collaborate with platform SMEs to validate and refine AI-generated outputs.
  • Design and maintain workflows for continuous learning and feedback loops between the AI and engineering teams.
  • Monitor AI performance and identify areas for improvement in accuracy, relevance, and usability.
  • Develop prompt templates and usage guidelines for engineers to interact effectively with Copilot.
  • Ensure compliance with data governance, security, and privacy standards.
  Qualifications:
  • 3+ years in platform engineering, DevOps, or technical documentation.
  • Familiarity with OutSystems, AutoRABIT, Azure APIM, or similar platforms.
  • Experience with AI/ML tools, prompt engineering, or knowledge management systems is a plus.
  • Strong analytical, communication, and organizational skills.
  Business Case for AI-Supported Platform Engineering
  Objective:
  To enhance platform reliability, reduce MTTR (Mean Time to Resolution), and improve engineering productivity through AI-assisted knowledge management and operational support.
  Key Benefits:
  Operational Efficiency
  • Instant access to historical tickets, change logs, and documentation.
  • Automated summarization and contextual answers reduce time spent searching for information.
  Break/Fix Acceleration
  • AI can suggest known fixes, identify patterns in recurring issues, and recommend escalation paths.
  • Reduces dependency on tribal knowledge.
  Onboarding & Training
  • New hires can ramp up faster with AI-guided walkthroughs and contextual answers.
  • Reduces training overhead for senior engineers.
  Documentation Enhancement
  • AI can flag outdated or missing documentation based on user queries and gaps in responses.
  • Supports continuous documentation improvement.
  Scalability
  • AI scales with the team, providing consistent support regardless of team size or turnover.
  Strategic Insights
  • Analyze trends in platform issues, usage patterns, and support gaps to inform roadmap decisions.
  3. Outline: AI-Supported Platform Engineering Team Process
  Phase 1: Foundation
  • Hire AI Trainer
  • Audit existing documentation and ticketing systems
  • Define taxonomy and tagging standards for ingestion
  • Establish data governance and access controls
  Phase 2: AI Enablement
  • Ingest and structure documentation (internal, vendor, tickets, SOPs)
  • Train Copilot on platform-specific terminology and workflows
  • Develop prompt templates for common tasks (e.g., “How do I deploy to OutSystems staging?”)
  Phase 3: Integration
  • Embed Copilot into daily workflows (e.g., ticket triage, change request reviews)
  • Pilot with a small group of engineers
  • Collect feedback and iterate on AI responses
  Phase 4: Optimization
  • Implement feedback loops (e.g., thumbs up/down, correction suggestions)
  • Monitor usage metrics and accuracy
  • Expand to additional platforms or tools
  Phase 5: Continuous Improvement
  • Monthly knowledge base updates
  • Quarterly AI performance reviews
  • Annual retraining or fine-tuning based on platform evolution
  
  Metasys Technologies is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identify, national origin, veteran or disability status.
  

• About the company

  Metasys Technologies, Inc. (MTI) was founded in 2000 with the mission to provide best-in-class business and technology solutions to help companies win in the global marketplace. Starting with an initial focus on professional staffing and IT consulting,...

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