7 days ago
Base Salary
$190k - $346k/yr
Responsibilities
- Design and build large-scale batch and streaming data-processing pipelines for multimedia assets and model-derived signals.
- Set the technical vision and architecture for Firefly Foundry’s media-intelligence data platform and search stack.
- Architect hybrid lexical, vector, multimodal, and cross-modal retrieval with ranking, reranking, faceting, and metadata filtering.
- Build retrieval interfaces for AI agents, including tool/function-call retrieval, multi-hop planning, iterative retrieval, grounding, citations, and provenance.
- Own incremental and streaming indexing, backfills, reprocessing, schema versioning, and embedding-model versioning.
- Engineer enterprise capabilities including per-tenant index isolation, data residency, access controls, and audit support.
- Define retrieval quality gates, offline and online evaluation, regression detection, and drift monitoring.
- Own latency, throughput, freshness, recall, availability, and cost targets, including ANN tuning and accelerator capacity.
- Build deployment, observability, monitoring, alerting, incident response, and postmortem practices for data and search systems.
- Lead cross-team design and build-versus-buy decisions, mentor senior engineers, and represent the platform architecture to leadership and partner organizations.
Requirements
- 10+ years of experience in machine learning, data, or infrastructure engineering, including deep ownership of production-scale data processing and/or search and retrieval systems.
- Deep expertise with search and retrieval infrastructure, including vector/ANN retrieval, lexical search, hybrid retrieval, ranking, reranking, and query understanding.
- Strong data-engineering foundations in large-scale batch and streaming pipelines, data modeling, object stores, vector databases, and columnar or OLAP storage.
- Experience building retrieval for LLM and agentic systems, including RAG, multimodal and cross-modal search, grounding, provenance, and retrieval evaluation.
- Strong Python skills; Go, Rust, or C++ systems-language experience is a plus.
- Hands-on familiarity with embedding models and their inference paths, including PyTorch.
- Experience building observability, monitoring, and alerting for data and search systems with freshness, recall, and latency SLAs.
- Experience with multi-tenant systems and data isolation in enterprise or regulated environments.
- Fluency with Docker, Kubernetes, CI/CD, and AWS or Azure.
- Ability to reason about retrieval quality across text, image, video, 3D, and audio modalities.
- Proven technical leadership through mentoring, cross-organization architecture work, build-versus-buy decisions, roadmap influence, and standards setting.
- Excellent communication and data-driven problem-solving skills, including communication with leadership.
- 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.
Benefits
- Non-sales roles are eligible for Adobe’s Annual Incentive Plan.
- Certain roles may be eligible for a long-term new-hire equity award.
- Adobe provides comprehensive benefits programs and accessibility accommodations during the recruiting process.
Tech Stack
Categories
BackendData Engineering
About Adobe
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