Demonstrates expertise in building and optimizing large language models, with a strong focus on prompt engineering, system performance metrics, and user experience. Proficient in managing production systems, version control, and implementing governance practices for data handling.

Highest-signal resume keywords

Large Language ModelsPython ProficiencyLangChain and LangGraphProduction System OptimizationVersion Control and Governance

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Own YOlanda’s system prompt, including persona, tone, safety rules, refusals, and handoff behavior
Write and maintain prompts for V3 user actions, including plan changes, top-ups, balance queries, offers, troubleshooting, and account support
Design conversations to reach a product or service within five responses
Define YOlanda’s boundary of knowledge and create seamless handoffs to YOnC
Manage context about users, accounts, and plan catalogues; break tasks into chains and tool calls
Build and maintain bilingual evaluation sets with test cases, pass conditions, and trackable scores
Measure the YOlanda/YOnC boundary, fact-check plan and account information, and red-team top-up and rewards flows
Trace calls and monitor prompt versions, models, tokens, cache hits, latency, and cost
Set latency and availability SLOs and build alerts
Own gateway timeouts, retries, and provider/model fallbacks
Design cacheable prompts and build semantic, retrieval, and tool-result caching with correct scoping and invalidation
Optimize token budgets, context trimming, output length, and batch APIs
Benchmark and route frontier and open models by task based on accuracy, latency, and cost
Collaborate with engineers running open models on YOnC compute
Keep prompts, models, and configuration versioned, reviewed, tested, owned, and rollback-ready in git
Build CI release gates, canary deployments, staged rollouts, and kill switches
Audit account- and money-related actions and redact personal data before logging or sending to third-party providers
Implement runtime guardrails including prompt-injection defenses, tool permissions, spend limits, and human-approval points
Set cost budgets per feature and model with alerts and translate AI/money/operator-account rules into code controls
Open pull requests against the LangChain and LangGraph build alongside the two owning engineers
Work daily in models and production without managing people

Requirements

What you’ll need

Two or more years building with large language models in production, at real traffic
Python proficiency, including scripts, API clients, data handling, and tests
Git, JSON, regex, and Markdown
Shipped production systems with LangChain and LangGraph; able to read and modify an unfamiliar graph safely
Experience writing and shipping system prompts and building evaluation harnesses
Ability to change one variable at a time and record results
Production experience with tracing, SLOs, fallbacks, and correctly invalidated caching
Demonstrated before-and-after improvements in cost and latency with quantified results
Practical governance experience with versioning, release gates, audit logging, and personal data handling
Production retrieval experience with chunking, embeddings, reranking, and grounding answers in sources; knowing when retrieval is inappropriate
Exceptional written English, including syntax, register, and nuance
Care for users, particularly prepaid-plan users who count every dollar

Benefits

Comp & perks

Flexible working hours
Competitive salary
Real opportunity for personal and professional growth

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Prompt EngineeringAPI Client DevelopmentData HandlingTracing and MonitoringSLO ManagementCaching StrategiesQuantitative AnalysisEvaluation HarnessesChunking and EmbeddingsAudit Logging

Soft Skills

Exceptional Written EnglishUser-Centric Approach

Tools & Technologies

GitJSONRegexMarkdown

Industry Keywords

Production SystemsCost ManagementLatency OptimizationData PrivacyAI Governance