• 10+ years in machine learning, data, or infrastructure engineering, including deep ownership of large-scale data processing and/or search & retrieval systems in production - and a track record of leading systems and setting technical direction across teams.
• Deep expertise designing and operating search and retrieval infrastructure at scale - vector/ANN (e.g., HNSW, IVF, ScaNN, DiskANN), lexical search (Lucene / Elasticsearch / OpenSearch), hybrid retrieval, ranking and reranking, and query understanding.
• Strong data-engineering foundations - large-scale batch and streaming pipelines (e.g., Spark, Beam, Flink, Ray), data modeling, and the storage systems behind them (object stores, vector databases, columnar/OLAP).
• Experience building retrieval for LLM and agentic systems - RAG, multimodal and cross-modal search, grounding and provenance, and retrieval evaluation.
• Strong Python, plus a systems language (Go, Rust, or C++) a plus; hands-on familiarity with embedding models and the inference paths that produce them (PyTorch).
• A track record building the observability, monitoring, and alerting that data and search systems rely on to hit freshness, recall, and latency SLAs.
• Experience with multi-tenant systems and data isolation in an enterprise or regulated context.
• Fluency with containers and orchestration (Docker, Kubernetes), CI/CD, and a major cloud (AWS or Azure).
• Comfort reasoning about retrieval quality and relevance across modalities (text, image, video, 3D, audio), in partnership with Applied Science.
• Proven technical leadership - mentoring senior engineers, driving cross-org design and build/buy decisions, and influencing roadmap and standards.
• Excellent communication and data-driven problem-solving in cross-functional settings, including with leadership.

Education

• MS or PhD in Computer Science, Computer Engineering, or a related field - or equivalent practical experience building and operating large-scale data and search systems.

FireflyGenAI

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $190,200 – $345,650 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

In California, the pay range for this position is $238,700 - $345,650 In New York, the pay range for this position is $238,700 - $345,650 In Washington, the pay range for this position is $223,500 - $323,700

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

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