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The Event for the Autonomous AI Era
AI Context Engineer
Location
United States
Posted
83 days ago
Salary
0
Seniority
Senior
Job Description
AI Context Engineer
AGENTIC
• 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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• Design and maintain an AI technology stack that supports automated customer life cycles and product-led engagement • Unify customer data into a definitive system of record to power all automated communications and buyer journeys • Evaluate and implement AI tools and data constructs that solve specific friction points in the freemium and trial conversion process • Establish data pipelines and model governance to ensure reliable, scalable, and automated insights • Implement AI-driven experiences within the application to communicate directly with users based on real-time behavior • Develop AI-powered health monitoring and expansion strategies to drive engagement beyond the initial sales meeting • Scale operations through automation, focusing on 'human-in-the-loop' workflows rather than managing a large manual team • Provide recommendations to product and marketing teams on building the foundation for new, automated GTM motions • Serve as the AI subject matter expert, 'charting the path' for growth by translating business requirements into technical AI solutions • Conduct a 90-day 'listening tour' to map out current onboarding processes, data availability, and build customer empathy • Establish performance metrics and continuously optimize AI models based on business outcomes and ROI

