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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in product ownership and AI application development, with a strong focus on delivering production-grade LLM solutions while ensuring compliance and data governance. Capable of translating complex requirements into actionable user stories and managing cross-functional teams effectively.
Highest-signal resume keywords
Product Ownership ExperienceProduction LLM ApplicationsModel Evaluation MethodologiesTechnical User Stories in JiraC1+ English 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 Use Case DefinitionPrompt EngineeringModel EvaluationAPI RequirementsBacklog GroomingRisk ManagementData Privacy ComplianceTechnical Trade-offsDocument ExtractionConversational AI
Soft Skills
Exceptional CommunicationStakeholder EngagementTeam LeadershipProblem SolvingAdaptability
Tools & Technologies
Azure AILangChainLlamaIndexLangSmithPhoenixArizeJiraConfluence
Industry Keywords
FintechFinancial ServicesCompliance-sensitive EnvironmentsCloud Consumption BudgetsSystem Reliability
Tech Stack
Tools & technologiesAzureCloud
About the role
Key responsibilities & impact- Define, prioritize, and drive production-grade AI use cases based on technical feasibility and business ROI
- Translate raw requirements into user stories with robust acceptance criteria and edge-case coverage
- Curate golden evaluation datasets with subject matter experts
- Monitor hallucination risks and refine prompts, guardrails, and context retrieval systems
- Lead sprint planning, backlog grooming, and release cycles across AI research, data engineering, frontend development, and DevOps teams
- Balance product innovation, latency, and cloud consumption budgets
- Direct technical workshops, product demos, and executive check-ins
- Secure data privacy and governance sign-offs in compliance-sensitive enterprise environments
- Track project milestones, manage LLM token costs and infrastructure dependencies, and maintain transparent risk logs
- Protect system reliability and budget constraints
Requirements
What you’ll need- 4+ years of product ownership experience
- Proven track record delivering modern software products
- Hands-on experience shipping production LLM applications, such as AI agents, RAG architectures, document extraction, or conversational AI
- Solid understanding of model evaluation methodologies, prompt engineering workflows, vector search, guardrails, and observability metrics including accuracy, token consumption, and latency
- Experience crafting technical user stories, API requirements, and decision logs in Jira and Confluence
- Demonstrated capability to interface with North American executive stakeholders
- Ability to articulate complex technical trade-offs and navigate regulated business environments
- Exceptional written and verbal C1+ English skills
- Experience with Azure AI, LangChain, LlamaIndex, LLM observability platforms such as LangSmith, Phoenix, or Arize, or fintech/financial services environments is a strong plus
Benefits
Comp & perks- Continuous multi-project pipeline
- Agentic AI tools and training
- Coursera Enterprise
- Studio practice labs
- L1-L7 Career Framework
- High-touch onboarding
- Transparent leadership communication
- Community recognition
- Psychological safety
- 100% remote work
- Competitive pay in USD
- Holidays off and paid time off
- Health insurance assistance program
- Opportunity to work with high-growth US-based companies and cutting-edge tech stacks