AI Engineer/Forward engineer
RAG / Search
31 open positions across the agentic economy.
A RAG (Retrieval-Augmented Generation) or Search engineer builds the retrieval layer that grounds language models in private or up-to-date data: chunking strategies, embedding models, vector indices, hybrid lexical+semantic ranking, and the LLM-side prompting that turns retrieved passages into trustworthy answers. The role is increasingly its own specialty as enterprise AI deployments hit the limits of naive RAG and need re-rankers, query rewriting, and evaluation harnesses. Strong candidates know information-retrieval fundamentals (BM25, Reciprocal Rank Fusion) and have shipped a production RAG system end-to-end.
As of August 2026, AgenticCareers tracks 31 open RAG / Search positions across 24 companies. The median advertised salary is $127K–$200K per year (based on 12 listings with disclosed pay). 26% of roles are remote. The most active employers are Capital One, Meta, Databricks.
Full RAG / Search salary dataRAG / Search
AI Agent · RAG
RAG / Search · Executive
AI · ai agent · rag
RAG · Machine Learning
Meta is seeking a Software Engineer to join the MTIA (Meta Training & Inference Accelerator) Software Tooling team, which develops and maintains the tooling ecosystem for Meta's in-house AI accelerator ASICs. The Tooling team provides debugging, profiling, memory analysis, and monitoring capabilities for the whole MTIA Ecosystem, advancing ML accelerator tooling by leveraging Meta's full-stack ownership from silicon specs to fleet observability. In this role, you will be a senior technical contr
Meta is seeking a Software Engineer to join the MTIA (Meta Training & Inference Accelerator) Software Tooling team, which develops and maintains the tooling ecosystem for Meta's in-house AI accelerator ASICs. The Tooling team provides debugging, profiling, memory analysis, and monitoring capabilities for the whole MTIA Ecosystem, advancing ML accelerator tooling by leveraging Meta's full-stack ownership from silicon specs to fleet observability. In this role, you will be a senior technical contr
RAG / Search
RAG / Search
AI · ai agent · rag
RAG / Search
RAG / Search
RAG / Search
RAG / Search · Executive
RAG / Search
rag
rag
RAG / Search
RAG / Search
rag
ai agent · rag
RAG · Machine Learning
Job Summary Westfield is hiring an AI Engineer to build AI use cases of different shapes and sizes that impact our core insurance workflows. You’ll work with other AI Engineers, software developers, and business stakeholders to ship features and assets that range in complexity from simple prompt workflows and document understanding to AI agents, RAG, computer use, and more. You’ll be involved in business use cases from design and architecture into implementation, testing, deployment, monitor
RAG / Search
RAG / Search
api · CSS · docker
RAG / Search
RAG / Search
RAG / Search
RAG / Search
A RAG (Retrieval-Augmented Generation) or Search engineer builds the retrieval layer that grounds language models in private or up-to-date data: chunking strategies, embedding models, vector indices, hybrid lexical+semantic ranking, and the LLM-side prompting that turns retrieved passages into trustworthy answers. The role is increasingly its own specialty as enterprise AI deployments hit the limits of naive RAG and need re-rankers, query rewriting, and evaluation harnesses. Strong candidates know information-retrieval fundamentals (BM25, Reciprocal Rank Fusion) and have shipped a production RAG system end-to-end.
As of August 2026, AgenticCareers tracks 31 open RAG / Search positions across 24 companies, updated daily.
The median advertised RAG / Search salary is $127K–$200K per year, based on 12 listings with disclosed pay.
26% of the RAG / Search roles currently tracked on AgenticCareers are remote.
The most active employers hiring RAG and Search engineers right now are Capital One, Meta, Databricks.
What Is a RAG Engineer? Role, Skills, Salary & How to Become One (2026)
A RAG Engineer builds retrieval pipelines that ground LLMs in source documents. Here's what they do day-to-day, typical salary ($160K-$340K), the skills you need, and how to transition from SWE or ML engineer roles.
RAG vs. Fine-Tuning: A Decision Framework for 2026
Should you retrieve context at inference time or bake knowledge into the model? This guide provides a concrete decision framework with cost, accuracy, and maintenance trade-offs for each approach.
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