AI Engineer Top Skills/Phrases

Top technical and professional skills and phrases for ai engineer roles.

Top Skills/Phrases

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 production LLM applications from problem framing through deploymentDesign prompts, system instructions, and context windows with versioned testsImplement RAG ingestion, chunking, indexing, retrieval, reranking, and groundingDesign agent workflows with tools, memory, planning, permissions, and fallbacksSelect and evaluate foundation models for quality, latency, cost, and safetyAdapt models with fine-tuning, PEFT or LoRA, and distillation when justifiedCreate evaluation datasets, automated metrics, human review, and regression gatesEngineer embeddings and vector search with hybrid retrieval and relevance tuningDevelop Python services, APIs, SDK integrations, and asynchronous or streaming workflowsBuild reliable data pipelines for structured, unstructured, and multimodal dataOperate cloud GPU or accelerator workloads with containers, orchestration, and cost controlsImplement LLMOps or MLOps CI/CD, version management, release gates, and rollbackInstrument observability for traces, tokens, retrieval quality, latency, and failuresSecure AI systems against prompt injection, data leakage, unsafe tools, and authorization flawsApply responsible AI, privacy, governance, documentation, and incident-response practicesDesign scalable distributed systems with caching, queues, rate limits, and resilienceOptimize inference with batching, caching, quantization, routing, and model choiceTranslate domain workflows into measurable AI product requirements

Behavioral Skills/Phrases

Professional skills and phrases that help candidates collaborate, communicate, and grow into senior roles.

Problem framing under ambiguityEvidence-based judgmentClear technical communicationCross-functional collaborationCustomer and domain empathyResponsible risk ownershipExperimental disciplineLearning agilityPragmatic trade-off decision-makingIncident composureDocumentation and knowledge sharingStakeholder expectation managementStakeholder ManagementTechnical CommunicationCustomer-Facing EngineeringProblem SolvingCritical ThinkingSystems ThinkingOwnershipLeadershipMentoringAgile DeliveryRisk Management

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