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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 deploying AI agents that enhance business workflows, with a strong focus on backend development, production-grade AI systems, and integration of external data sources.
Highest-signal resume keywords
AI Agent DevelopmentProduction-Grade SystemsPython ProgrammingCloud-Native ArchitectureREST API Integration
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 EngineeringAI/LLM SystemsMulti-Step ReasoningTool-CallingOrchestrationTask Evaluation FrameworksMemory ManagementDistributed SystemsData AnalysisAutomation
Tools & Technologies
Cloud PlatformsVector Store SolutionsMCPsAI Agents EcosystemHuman-in-the-Loop Systems
Industry Keywords
Quantitative DisciplineEngineeringMathematicsPhysicsBusiness Impact
Tech Stack
Tools & technologiesCloudDistributed SystemsPython
About the role
Key responsibilities & impact- Design, build, and deploy AI agents that automate and augment high-value workflows across business functions.
- Own the end-to-end agent stack, including tool use, memory management, multi-step planning, human-in-the-loop escalation patterns, guardrails, and audit trails.
- Define agent evaluation frameworks measuring task completion, accuracy, hallucination rates, latency, and business impact.
- Iterate on agent behavior using real usage data and stakeholder feedback.
- Implement integrations allowing agents to take automated actions on behalf of users.
- Collaborate with engineering teams to design, build, and maintain production pipelines.
Requirements
What you’ll need- Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or a related quantitative discipline.
- 5+ years of software engineering experience, with proven ability to build production-grade systems beyond research, experimentation, or prompt engineering.
- Hands-on experience building and operating production-grade AI/LLM systems, ideally including agentic workflows, tool-calling, orchestration, evaluations, or multi-step reasoning systems.
- Strong backend expertise, including Python, distributed systems, and cloud-native architecture.
- Familiarity with the AI Agents ecosystem, including different LLM providers, vector store solutions, MCPs, A2A and more.
- Familiarity with REST APIs and integrating external data sources.