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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 implementing Agentic AI systems and LLM applications, with a strong focus on problem-solving and delivering business value. Proficient in collaborating with cross-functional teams to ensure AI solutions are reliable, explainable, and aligned with enterprise standards.
Highest-signal resume keywords
Agentic AI System DesignLLM Application DevelopmentPython ProgrammingAI/ML Solutions DeliveryCommunication Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI Agent DesignMulti-Agent SolutionsProcess AutomationUnstructured Text ProcessingEvaluation and MonitoringRisk ManagementMachine LearningData ScienceTool OrchestrationBusiness Problem Solving
Soft Skills
Excellent CommunicationMentoring
Certifications & Qualifications
MS or PhD in Computer ScienceMachine LearningData Science
Industry Keywords
Enterprise AI SolutionsResponsible AI StandardsCross-Functional CollaborationBias and Drift MonitoringEvaluation Guardrails
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Partner with business stakeholders to identify, frame, and prioritize high-value problems addressable using Agentic AI, LLMs, and NLP
- Translate business needs into AI use cases, success metrics, and delivery plans
- Architect and develop agentic AI systems that reason, plan, and act across tools, workflows, and data sources
- Design multi-agent and tool-augmented LLM solutions for complex, multi-step process automation
- Ensure AI solutions are reliable, explainable, and governed for enterprise use
- Collaborate with engineering teams to deploy scalable, secure, and performant AI solutions
- Implement evaluation, monitoring, and guardrails for LLM and agentic systems, including bias, drift, and failure modes
- Align solutions with enterprise risk management, compliance, and responsible AI standards
- Advise teams on where Agentic AI and LLMs add value
- Contribute to AI best practices, reusable patterns, and strategic direction
- Mentor peers and teammates on applied AI and business-driven problem solving
Requirements
What you’ll need- Experience designing AI agents that reason, plan, and act across systems
- Hands-on experience building enterprise LLM applications, including RAG, tool use, orchestration, and evaluation
- Strong experience working with unstructured text and language-driven workflows
- MS or PhD in Computer Science, Machine Learning, Data Science, or a related quantitative field
- 3+ years delivering AI/ML solutions in production environments
- 5+ years of hands-on Python experience
- Strong ability to solve business problems using AI, not just build models
- Excellent communication skills, with ability to explain complex concepts to technical and non-technical audiences
- Experience working in cross-functional, enterprise environments
- Visa sponsorship is not offered
Benefits
Comp & perks- Hybrid working model designed to provide flexibility while enabling in-person learning, collaboration, and connection
- Opportunities to learn and develop skills as individuals and as a team
- Mission-driven, highly collaborative culture
- Long-term financial wellbeing focus