Senior AI Application Engineer

Job not on LinkedIn

🕒 July 7

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

💻 Application Engineer

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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DISHER

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2000

🚘 Automotive

💼 Consulting

Automotive • Consulting • Engineering

DISHER is a solutions-focused company with over 20 years of experience in making a positive difference through engineering and product development. They offer a range of services including electronics, manufacturing technology, business consulting, and talent solutions with a human-centered and innovative approach. DISHER specializes in solving complex problems with cross-functional teamwork, providing top engineering and technical talent to advance projects. They serve various industries such as Medical, AgTech, and IoT, and are committed to community investment and creating a thriving workplace culture.

📋 Description

• 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 and context quality • Tune retrieval pipelines (hybrid search, vector search, filters, reranking) for accuracy, latency, and cost • Build and maintain prompt orchestration frameworks, including dynamic prompt assembly and context injection • Ensure strong grounding and citation mechanisms so model outputs are traceable and verifiable • Design and implement AI agents and agentic workflows, including tool use, planning, and multi-step task execution • Integrate agents with internal and external systems (APIs, databases, SaaS tools) to enable real-world actions • Define and implement evaluation frameworks (offline & online) to measure retrieval quality, agentic performance, and answer correctness • Design and enforce guardrails (safety, hallucination reduction, policy compliance) across generation and agentic behavior • Collaborate with product, data, and platform teams to integrate AI capabilities into applications • Monitor system performance and continuously iterate based on user feedback and metrics • Partner with business and technology leadership to identify, evaluate, and prioritize agentic AI opportunities across Flash's operations • Translate business problems into AI system designs - scoping what's feasible, defining the data requirements, and owning delivery • Build repeatable patterns and internal tooling that accelerate future AI development across the organization • Contribute to Flash's evolving AI governance and responsible use practices

🎯 Requirements

• Experience building or maintaining RAG systems in production environments • Experience with hybrid search (keyword + vector) and reranking models • Knowledge of evaluation frameworks (e.g. RAGAS, LLM-as-a-judge approaches) • Experience integrating agents with enterprise tools (CRM, ERP, ticketing systems, etc.) • Experience optimizing systems for scale, latency, and cost • Strong knowledge of search technologies (Azure AI Search, Elasticsearch, or similar) • Hands-on experience with LLMs, embeddings, and vector databases • Experience designing and deploying AI agents or agentic systems • Demonstrated ability to integrate agents with enterprise systems - ERP, CRM, ticketing, or similar operational platforms • Understanding of information retrieval concepts (ranking, relevance, recall/precision tradeoffs) • Experience with prompt engineering and LLM orchestration tools • Familiarity with evaluation techniques for generative AI and agent systems • Ability to translate ambiguous business problems into concrete AI system designs • Ability to balance experimentation with production reliability • Hands-on experience building AI agents and agentic workflows, including tool use, multi-step reasoning, and orchestration across APIs and services • Understand how to design systems that can plan, retrieve context, take actions, and operate within defined guardrails in production environments • Proven ability to build effective, reliable AI agents that complete real-world tasks safely and accurately • Ability to provide measurable improvements in retrieval relevance and system performance • Previous experience creating robust guardrails and evaluation systems that catch issues early • Experience building scalable, maintainable architecture integrated into core products • Self-starter that thrives on ownership • Must have the current and continuing right to work in the United States of America without restrictions or expirations

🏖️ Benefits

• Supportive, collaborative environment • Opportunities for technical and personal advancement • Focus on work-life balance and professional development