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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and building autonomous AI agents and multi-agent systems, with a strong focus on machine learning model deployment and operational efficiency in cloud environments. Proficient in Python and familiar with LLM capabilities, evaluation frameworks, and data governance.
Highest-signal resume keywords
Python ProgrammingMachine Learning Pipeline ManagementLLM-Based Systems DeploymentCloud Environment OperationsMulti-Agent System Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringBackend EngineeringMachine LearningInfrastructure Policy DetectionScaling PredictionGPU Configuration RecommendationsData GovernanceEvaluation FrameworksAgentic FrameworksRetrieval Systems
Soft Skills
Strong OwnershipCollaboration
Tools & Technologies
SlackJiraCursorWindsurfAI-Powered IDEs
Industry Keywords
Autonomous AI AgentsInfrastructure AnalysisCost OptimizationFinOpsOperational Data
Tech Stack
Tools & technologiesCloudPython
About the role
Key responsibilities & impact- Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions
- Develop multi-agent systems for troubleshooting, optimization, FinOps, and how-to use cases
- Use LLM capabilities including tool use, memory, and retrieval safely in production
- Develop MCPs exposing ScaleOps capabilities to AI agents
- Build integrations with Slack, Jira, Cursor, Windsurf, and other AI-powered IDEs
- Build and deploy machine learning models for infrastructure policy detection, scaling prediction, and GPU configuration recommendations
- Own the complete ML pipeline from training through production
- Build internal AI tools for engineering, development, research, and support
- Develop AI-powered tools for Sales and Support teams, including infrastructure analysis and cost optimization reports
- Own AI systems from concept to production, targeting sub-2-second responses, reliability, safety, and cost-effectiveness
- Build evaluation frameworks and implement security controls
- Define AI architecture and best practices as a founding member of the AI team
- Make technical decisions on frameworks, multi-agent systems, and data governance
Requirements
What you’ll need- Significant software engineering experience (typically 4+ years)
- Strong Python skills and solid backend engineering fundamentals
- Experience building and operating production systems in cloud environments
- Practical experience bringing LLM-based systems into production, including handling latency, cost control, and failure modes
- Familiarity with agentic frameworks such as LangChain and MetaGPT
- Familiarity with evaluation frameworks
- Strong ownership and ability to operate independently while collaborating closely across teams
- Experience with structured or operational data such as configurations, logs, and metrics
- Experience with retrieval systems (RAG) or vector databases (advantage)