AGENTIC

The Event for the Autonomous AI Era

AI Context Engineer

Artificial IntelligenceArtificial IntelligenceContractRemoteTeam 11-50Since 2017H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

7 days ago

Salary

Not specified

EnglishPythonType Script

Job Description

• Design and implement context pipelines for LLM-based systems. • Structure information to maximize model understanding and response quality. • Define strategies for prompt composition, context injection, and tool usage. • Build and optimize RAG pipelines using vector databases. • Implement document ingestion, chunking, embedding, and retrieval strategies. • Improve retrieval precision and reduce hallucinations in AI outputs. • Design and maintain prompt frameworks for AI agents and applications. • Optimize prompts through systematic testing and evaluation. • Integrate prompts with tool use, APIs, and agent workflows. • Structure knowledge bases for AI consumption. • Implement pipelines for data preprocessing, indexing, and embedding generation. • Manage semantic search and knowledge retrieval systems. • Analyze model performance and improve context efficiency. • Monitor latency, token usage, and system scalability. • Develop evaluation methods to measure prompt and context performance. • Work closely with AI Engineers, Data Engineers, and Product Teams. • Translate business requirements into AI-powered solutions. • Document context architectures and AI workflows.

Job Requirements

  • Strong experience working with LLMs (OpenAI, Anthropic, open-source models, etc.)
  • Experience building RAG systems
  • Knowledge of vector databases (Pinecone, Weaviate, Qdrant, Chroma, etc.)
  • Understanding of embeddings and semantic search
  • Experience with prompt engineering and prompt evaluation
  • Programming skills in Python or TypeScript
  • Experience with API integrations
  • Understanding of LLM limitations, hallucinations, and context windows
  • Knowledge of token optimization strategies
  • Familiarity with agent frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.)
  • Experience working with structured and unstructured data
  • Knowledge of JSON, APIs, and data pipelines
  • Strong analytical and problem-solving mindset
  • Ability to experiment and iterate rapidly
  • Clear technical documentation skills

Benefits

  • Health insurance
  • Retirement plans
  • Paid time off
  • Flexible work arrangements
  • Professional development

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