Level

Databricks

Senior Staff Software Engineer- Search Quality

Databricks is hiring a Senior Staff Software Engineer- Search Quality in Bengaluru, India. Level rates it ; you can apply on Databricks.

Level's read on this job

  • On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
  • The posting mentions RAG, AI agents and fine tuning among its tools and skills.
  • Level classes it as a lead role.
  • Databricks has 894 other open roles on Level.

AI in this role

ragai-agentsfine-tuning

P-1408

The Mission

We are democratizing Data and AI for every enterprise user. Our vision is a world where anyone can master their organization’s data through Apps and AI Agents. We are building the retrieval backbone for two worlds: the high-precision context layer for AI agents and the intuitive search experience for people goal is the same: instant, accurate, and actionable insight.

 

The Role: 

  • As a Search Quality Engineer, you sit at the heart of this transformation. You aren't just building a search engine; you are building the contextual backbone of the entire company.
  • You will own the quality of results for two distinct but deeply connected "users":
  • The AI Agent: Optimizing the retrieval layer that allows LLMs to reason over data they weren’t trained on, ensuring they have the "ground truth" needed  to synthesize accurate, high-stakes business actions.
  • The Human User: Improving the traditional search experience so employees can find assets and answers through intuitive, high-recall interfaces.

The Technical Challenge

This isn't a solved problem. You will be tackling "Search" in its most evolved form:

  • Hybrid Retrieval: Balancing traditional keyword-based search (for exactness) with semantic vector search (for intent).
  • Dual-Optimization: Fine-tuning ranking models that satisfy both human readability and LLM-ready context.
  • High-Stakes Accuracy: In a world of Agents, poor search quality leads to hallucinations. You will build the guardrails and relevance scoring that ensure our AI stays grounded in reality.
  • Data Heterogeneity: Connecting the dots across structured SQL tables, unstructured docs, and real-time business metrics.

Why This is the Place to Be

  • You will have a front-row seat to the Agentic revolution. If you want to solve the hardest problems in data discovery and see your work power the decision-making of thousands of people, let’s talk.

 

What We’re Looking For

  • The IR Specialist: You know your way around Lucene/Elasticsearch, embeddings, and ranking algorithms.
  • The Quality and Metrics Obsessive: You understand that "relevance" is subjective and love building evaluation frameworks (human-in-the-loop and LLM-based) to measure it. You are obsessed with relevance metrics (nDCG, MRR, Precision@K).
  • The Bridge Builder: You’re excited to apply traditional Information Retrieval (IR) wisdom to the cutting-edge world of Retrieval-Augmented Generation (RAG).

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.

How we rate this

Senior Staff Software Engineer- Search Quality at Databricks rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsFine-tuning

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$167k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: RAG, AI agents, and Fine-tuning. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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