Senior AI Application Engineer
New
RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- ElasticSearchPrompt Engineering
Requirements
- Proven experience building or maintaining RAG systems in production environments.
- Strong knowledge of search technologies such as Azure AI Search or Elasticsearch.
- Hands-on experience with LLMs, embeddings, and vector databases.
- Experience designing and deploying AI agents and agentic workflows.
- Familiarity with hybrid search, keyword + vector search, and reranking models.
- Knowledge of evaluation frameworks such as RAGAS or LLM-as-a-judge.
- Experience integrating AI agents with enterprise tools like CRM, ERP, or ticketing systems.
- Ability to design systems for scale, latency, and cost-efficiency.
- Experience with prompt engineering and LLM orchestration tools.
- Ability to translate ambiguous business problems into concrete AI system designs.
Responsibilities
- Own the end-to-end RAG pipeline, from data ingestion to response generation.
- Design and implement Azure AI Search indexing strategies, including schema design, scoring profiles, and performance optimization.
- Develop and refine chunking and metadata strategies to maximize retrieval relevance.
- Tune retrieval pipelines, including hybrid search, vector search, and reranking, for accuracy and latency.
- Design and implement AI agents and workflows involving tool use, planning, and multi-step execution.
- Integrate agents with enterprise systems like CRM, ERP, and databases.
- Build evaluation frameworks and safety guardrails to measure and ensure model correctness.
- Collaborate with business leadership to prioritize AI opportunities and define data requirements.
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