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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading complex technical programs, translating AI priorities into actionable plans, and coordinating cross-functional teams. Proficient in Python, SQL, and LLM SDKs, with a strong focus on evaluating risks and ensuring deployment readiness in regulated environments.
Highest-signal resume keywords
Complex Technical Program LeadershipPython ProgrammingLLM SDK PrototypingData Modeling and IntegrationRisk Assessment and Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonSQLAPIsGitTestingData ModelingMulti-Step OrchestrationLLM SDKRAG ExperienceVector Database Experience
Soft Skills
Influencing Without AuthorityMentoringEscalation Management
Tools & Technologies
OpenAI SDKGoogle SDK
Industry Keywords
FintechData-Sensitive SettingCX MetricsSupport MetricsCompliance Metrics
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Translate AI priorities into technical plans with scope, requirements, milestones, success metrics, acceptance criteria, and named owners
- Turn incomplete briefs into testable hypotheses, baselines, and measurable outcomes
- Coordinate technical dependencies across Engineering, Product, Data, FDE, AI Enterprise, and platform teams
- Drive technical decisions with engineers, challenge assumptions, make trade-offs explicit, and record outcomes
- Manage execution and risk by tracking commitments, removing blockers, and escalating early with recommendations
- Coordinate evaluations and deployment readiness, including quality, latency, cost, and permissions risks
- Verify that FDE integrations work in the receiving team’s environment
- Secure named owners for support, monitoring, and maintenance
- Measure whether each solution solved the intended problem
- Work with AISec and the AI Governance Committee so reviews happen early
- Turn project lessons into reusable briefs, checklists, decision records, and handoff standards
- Report to the Head of AI Enablement & Talent Development
Requirements
What you’ll need- Proven experience leading complex technical programs or software delivery across several teams, with specific examples of personal judgment, design contributions, decisions, and results
- Practical skills in Python, SQL, APIs, authentication, Git, and testing
- Comfortable using at least one LLM SDK, such as OpenAI or Google, to prototype integrations and debug issues
- Understanding of data modeling, pipelines, and enterprise integration patterns
- Experience with tool calling, multi-step orchestration, state, structured outputs, human review, and fallbacks
- Ability to assess quality, latency, cost, and permissions risks, and define useful evaluations
- Ability to establish baselines, validate assumptions through experiments, and balance sophistication with operational constraints
- Track record of translating between business and engineering teams, influencing without formal authority, mentoring others, and escalating decisions early
- Examples of solution designs, evaluation decisions, or delivery outcomes
- Applied LLM work used by real users
- RAG and vector database experience
- Experience deploying into environments owned by other teams
- Experience in a regulated or data-sensitive setting such as fintech
- Experience with CX, support, or compliance metrics such as AHT, FCR, CSAT, and SLA
Benefits
Comp & perks- Initial stock options grant
- Annual performance bonus
- Unlimited PTO
- Paid parental leave
- Hybrid work setup
- Health, dental, and vision plans
- Continuous learning opportunities
- Empowering opportunities for growth in a dynamic entrepreneurial environment