1,000+ matching jobs for “Senior AI Engineer”How results work Exact titles rank first, then title variations and keywords in descriptions. These labels aren't qualification scores. Without keywords, recently added jobs appear first.
NVIDIA is well positioned as the 'AI Computing Company', our GPUs being the brains that power modern Deep Learning software frameworks, …
Added Oct 27, 2026
NVIDIA is well positioned as the 'AI Computing Company', our GPUs being the brains that power modern Deep Learning software frameworks, …
Added Oct 27, 2026
+5 locations
Pay posted by employer $151,800–$265,350 per year
Build and deploy high-precision ML models for fraud and abuse detection, anomaly detection, and risk scoring. Engineer risk signals from large-scale account, device, network, behavioral, velocity, and session data. Integrate …
Added Oct 27, 2026
The Senior Cloud Software Development Engineer will lead the architecture, development, and delivery of cloud-native, …
Added Nov 10, 2026
+4 locations
include implementing software and systems engineering practices to ensure high efficiency and availability of AI systems. As a senior DGX Cloud AI Infrastructure software engineer at NVIDIA, you will have the opportunity …
Added Oct 27, 2026
Pay posted by employer $164,600–$288,000 USD
… sophisticated clients using leading technology and exceptional service. We are seeking a highly experienced Senior Principal Software Engineer to support technical development of our AI-powered Code Security Scanner …
Added Oct 16, 2026
Pay posted by employer $114,500–$194,700 USD
… sophisticated clients using leading technology and exceptional service. We are seeking a highly experienced Senior Lead Software Engineer to support technical development of our AI-powered Code Security Scanner platform. …
Added Oct 16, 2026
Pay posted by employer $110,000–$165,300 per year
… Enthusiasm for working directly with end-users and for figuring out to get the most out of the latest AI tools Preferred Experience deploying solutions through AI Factory, Pygentic, PowerApps Experience operating …
Added Oct 27, 2026
Pay posted by employer $296,300–$453,900
… shaping the future of transportation on a global scale. Role: As a Principal Technical Lead in the Embodied AI organization, you will be a senior individual contributor driving cutting-edge end-to-end machine learning …
Added Oct 12, 2026
Full time (company default) We are looking for a Sr. Staff ll, AI Native, AI First Engineer to pioneer and architect entirely new applications where Generative AI and Large …
Added Oct 4, 2026
+1 location
Pay posted by employer $228,600–$342,800 USD
… is quality you can't ship. Set technical direction and grow the team. Set the multi-year roadmap, mentor senior engineers, partner with Research, Product, and Platform leaders, and raise the technical bar across the …
Added Oct 4, 2026
+1 location
The Role The AI Quality and Productivity team in the Product Validation, Safety and Quality IT org is responsible for …
Added Oct 12, 2026
+1 location
The Role The AI Engineering and Productivity team in the Global Planning, Design, and Product IT org is responsible for …
Added Oct 12, 2026
Pay posted by employer $165,000–$180,000
The Senior AI Product Manager will lead product strategy, roadmap, and delivery for foundational AI platform solutions …
Added Nov 3, 2026
… pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their …
Added Nov 3, 2026
Pay posted by employer $159,900–$219,900 USD
As Senior Software Engineer, AI Native Web Platform on the Web Engineering team, you will build and scale the …
Added Oct 4, 2026
AI Application Support & Production Operations Provide operational support for production AI applications, …
Added Oct 15, 2026
We are looking for a Sr. Engineer to design, build, and scale the infrastructure powering NVIDIA’s AI agent ecosystem. You will work at the …
Added Oct 27, 2026
Your Career: Palo Alto Networks is seeking a Senior or Principal Backend Engineer (we are open to hire both levels) for our Cortex engineering group, focusing …
Added Oct 27, 2026
+4 locations
… team of engineers, research scientists, technical program managers, and product managers to deliver AI -powered products that change how our associates work and how our customers interact with Capital One. …
Added Oct 27, 2026
+1 more
Pay posted by employer $228,600–$342,800 USD
What We're Looking For · employer excerpt 10+ years of software engineering experience, with significant time spent building production retrieval, search, or RAG systems at scale. Deep Information Retrieval (IR) expertise: lexical retrieval (BM25, Lucene/Elasticsearch/OpenSearch), dense retrieval (embeddings, ANN indexes — FAISS, ScaNN, HNSW), hybrid retrieval, and learning-to-rank. Hands-on experience with modern LLM-era retrieval: RAG architectures, query rewriting, re-ranking with cross-encoders, long-context strategies, and grounding techniques that reduce hallucination. Experience designing agentic systems on top of retrieval — search planners, multi-hop / iterative retrieval, self-reflection and sufficiency checks, tool-using agents that decide what to fetch and verify what came back. Strong grasp of relevance evaluation: nDCG, MRR, Precision@K, Recall@K; offline/online experimentation; LLM-as-judge frameworks; building human labeling pipelines. 3 more in the full description below.
About this opportunity Original employer description P-1549
At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.
The Mission
Databricks agents are only as good as the context they can retrieve. Whether an agent is answering a question about last quarter's revenue, debugging a failing job, generating SQL against a 10,000-table lakehouse, or summarizing a Wiki page, its quality is bounded by what it can find — and how well it understands what it finds.
We are hiring a Senior Staff Applied AI Engineer to own context retrieval for Databricks agents across SaaS providers . This is a zero-to-one role with two deeply connected charters:
Build the retrieval stack — query understanding, content understanding, ranking, retrieval, and evaluation — across the Enterprise SaaS data stored across multiple systems.Build the search subagents that sit on top of that stack and reason about what context is needed , how to retrieve it , and whether the right thing actually came back — closing the loop between an agent's intent and the substrate that serves it.
If you have deep Information Retrieval wisdom, have shipped retrieval systems for RAG and agentic workloads, and want to build the substrate — and the agents on top of it — that make every Databricks agent measurably smarter, this role is for you.
What You Will Do
Build the full retrieval stack from scratch. Own the end-to-end system: query understanding, content understanding and indexing, hybrid retrieval, ranking, and evaluation. Make the architectural calls that will define how Databricks agents access context for years to come.Retrieve across heterogeneous data — structured and unstructured. Index and rank across structured assets (tables, columns, SQL queries, dashboards, code, notebooks, jobs) and unstructured content (docs, wikis, tickets, chat, images, video, audio). Each modality has its own signals — design retrieval that exploits them rather than flattens them.Connect to the SaaS surface area customers actually use. Build connectors and retrieval adapters for the systems where enterprise knowledge lives. Treat each retrieval source with its own freshness, permissions, and ranking signals.Optimize for two consumers at once. Retrieval must serve both LLMs (grounded, token-efficient, hallucination-resistant context) and humans (intuitive, explainable discovery). These are different objectives and require different signals — own both.Crack query understanding for agents. Agent queries don't look like web queries. Build query rewriting, decomposition, intent classification, and entity resolution tuned for multi-turn agentic workflows.Crack content understanding at scale. Build the pipelines that extract structure, entities, embeddings, summaries, and metadata from every supported asset type — and keep them fresh as customer data evolves.Build search subagents that reason about retrieval. Design the agentic layer that decides what context is needed , which sources to query , how to decompose and route the search , and — critically — whether the retrieved content is actually sufficient to answer the question . These subagents will plan multi-hop searches, issue follow-up queries when results are weak, ground claims against retrieved evidence, and hand back high-confidence context (or signal failure) to upstream agents. This is where IR meets agentic reasoning.Build the evaluation flywheel for both retrieval and subagents. Stand up offline evals (nDCG, MRR, Recall@K, Precision@K), LLM-as-judge harnesses, human-in-the-loop labeling, and online experimentation. Extend evaluation beyond ranking metrics to measure subagent decision quality — did it ask the right follow-up? , did it correctly recognize when retrieval failed? , did it ground its answer in the right evidence? . Quality you can't measure is quality you can't ship.Set technical direction and grow the team. Set the multi-year roadmap, mentor senior engineers, partner with Research, Product, and Platform leaders, and raise the technical bar across the org.
What We're Looking For
10+ years of software engineering experience, with significant time spent building production retrieval, search, or RAG systems at scale.
Deep Information Retrieval (IR) expertise : lexical retrieval (BM25, Lucene/Elasticsearch/OpenSearch), dense retrieval (embeddings, ANN indexes — FAISS, ScaNN, HNSW), hybrid retrieval, and learning-to-rank.
Hands-on experience with modern LLM-era retrieval : RAG architectures, query rewriting, re-ranking with cross-encoders, long-context strategies, and grounding techniques that reduce hallucination.
Experience designing agentic systems on top of retrieval — search planners, multi-hop / iterative retrieval, self-reflection and sufficiency checks, tool-using agents that decide what to fetch and verify what came back.
Strong grasp of relevance evaluation : nDCG, MRR, Precision@K, Recall@K; offline/online experimentation; LLM-as-judge frameworks; building human labeling pipelines.
Experience working across structured and unstructured data — you've indexed and ranked over tables, code, and documents in the same system, and have opinions about how to do it well.
Track record of building 0→1 : you've stood up a retrieval system from an empty repo, made the foundational architectural decisions, and grown it into something that customers depend on.
Demonstrated ability to operate as a technical leader : setting direction across teams, mentoring senior engineers, and influencing roadmap with research, product, and platform partners.
Nice to Have
Experience building retrieval over enterprise SaaS sources (permissions, freshness, multi-tenancy, ACL-aware indexing).
Background in agentic systems, tool use, or multi-turn retrieval for LLM agents.
Contributions to open-source IR/search projects, or publications at SIGIR, KDD, WWW, EMNLP, or similar venues.
Experience training or fine-tuning embedding models, rerankers, or query understanding models.
Why This Role
Foundational impact. Retrieval is the single biggest lever on agent quality. The stack you build will sit underneath every Databricks agent and every customer-built agent on our platform.Greenfield with scale. You get the rare combination of starting from a clean sheet and having immediate access to massive enterprise scale, real customer data, and a world-class research org.The right team. You'll work alongside engineers and researchers behind Lakehouse, Apache Spark™, Delta Lake, MLflow, MosaicML, and DBRX.
Location
This role is based in our Mountain View, CA or San Francisco, CA office. Hybrid in-office collaboration expected.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here .
Local Pay Range
$228,600 — $342,800 USD
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram .Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here .
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
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