Roles we place

AI engineering roles, matched to 2026 demand

From LLM product engineers to agent, RAG and MLOps specialists — hire the exact expertise your roadmap needs, on contract.

#1 fastest-growing

AI Engineer

Ships LLM-powered features into production — copilots, assistants and AI-native product flows.

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Core skills

PythonOpenAI & Anthropic APIsPrompt engineeringFunction callingStructured outputsStreaming UX

Typical use cases

  • In-app copilots & chat
  • Document Q&A
  • Workflow automation
  • AI-native features
+280% YoY demand

Agentic AI Engineer

Designs autonomous and multi-agent systems that plan, use tools and act across your stack.

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Core skills

LangChain / LlamaIndexAgent orchestrationTool & function useMCPPlanning & memoryGuardrails & evals

Typical use cases

  • Autonomous research agents
  • Ops & back-office automation
  • Multi-step workflows
  • Tool-using assistants
High demand

RAG Engineer

Grounds models in your data with retrieval-augmented generation that stays accurate and current.

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Core skills

Vector DBs (Pinecone, Weaviate, pgvector)Hybrid retrievalRerankingChunking & embeddingsEvaluationCitations

Typical use cases

  • Knowledge assistants
  • Support copilots
  • Internal semantic search
  • Policy & docs Q&A

Machine Learning Engineer

Trains, evaluates and deploys production ML — recommendations, ranking, forecasting and fraud.

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Core skills

PyTorch & TensorFlowFeature pipelinesModel servingRecommenders & rankingExperimentationSQL

Typical use cases

  • Recommendation engines
  • Fraud & anomaly detection
  • Demand forecasting
  • Ranking systems
Surging

MLOps / AI Platform Engineer

Deploys, monitors and scales AI in production — the infrastructure that turns demos into reliable systems.

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Core skills

CI/CD for MLDocker & KubernetesAWS / Azure / GCPObservability & tracingCost & latency tuningLLM gateways

Typical use cases

  • Deployment pipelines
  • Monitoring & evals in prod
  • Inference cost optimization
  • Platform reliability

GenAI / LLM Engineer

Fine-tunes, evaluates and optimizes large language models for your domain, latency and budget.

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Core skills

Fine-tuning & LoRAEval harnessesPrompt optimizationQuantizationDistillationLatency & cost tuning

Typical use cases

  • Domain-specialized models
  • Eval & quality systems
  • Inference optimization
  • Open-model deployment

Data Scientist

Turns data into decisions with rigorous analysis, experimentation and modeling.

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Core skills

StatisticsPython & SQLExperimentation / A-BForecastingVisualizationCausal inference

Typical use cases

  • Product & growth analytics
  • A/B testing
  • Forecasting & modeling
  • Decision support

Computer Vision Engineer

Builds vision systems — detection, segmentation, OCR and multimodal understanding.

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Core skills

PyTorch & OpenCVDetection & segmentationOCRMultimodal modelsEdge deploymentAnnotation pipelines

Typical use cases

  • Visual inspection & QA
  • Document & OCR pipelines
  • Video analytics
  • Multimodal search

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