See the top technical and behavioral skills and phrases desired by employers.
Technical Skills/Phrases
Core technical skills and phrases employers request most often.
Build tested Python services that integrate AI models through reliable APIsExplain language-model fundamentals and choose models that fit the taskDesign prompts and context that produce useful, controlled responsesBuild retrieval-augmented generation workflows using trusted source materialUse embeddings and vector search to retrieve relevant informationCreate tool-using agents with bounded actions and human approval pointsPrepare, validate and version data pipelines for AI applicationsAdapt pretrained models and compare the results against a clear baselineDesign repeatable evaluations for answer quality, safety and failure casesTest for harmful outputs, information leaks and unreliable model behaviorProtect sensitive data and control access to models, tools and servicesDeploy and scale AI workloads on cloud infrastructurePlan and run accelerator workloads within memory and computing limitsAutomate model and application releases with versioning and rollbackMonitor AI services through logs, traces, quality checks and alertsDebug failures across models, retrieval, application code and dataMeasure and improve response time, throughput and operating costDesign resilient AI systems with clear service boundaries and fallbacksReview, test and maintain code produced with AI assistanceDocument evaluation results, operational limits and reproducible experiments
Behavioral Skills/Phrases
Professional skills and phrases that help candidates collaborate, communicate, and grow into senior roles.
Turn an unclear business request into an agreed problem and success measureExplain AI limitations in language a nontechnical colleague can understandListen to users and revise a solution when their needs become clearerWork across software, data, security and product teams to deliver a serviceCompare options honestly before recommending a designRaise safety and privacy concerns early instead of hiding themTake responsibility for failures and help the team resolve themShare clear progress updates and ask for help before a deadline slipsUse feedback and test results to improve your next decisionPrioritize work by user value, risk and available resourcesKeep learning while checking new claims rather than following hypeTeach colleagues what you learned and document decisions for othersStakeholder communicationCritical thinkingCross-functional collaborationOwnershipUser empathyJudgmentAdaptabilityPrioritizationEthical reasoningContinuous learningMentoringAccountability
