Software Engineer, Digital Asset Management (DAM)

Quick Facts

• Role: Software Engineer, Digital Asset Management (DAM)

• Focus: Backend distributed systems + ML/generative AI for enterprise asset platforms

Description

You will design and develop next-generation enterprise asset platforms that manage, transform, index, and distribute massive volumes of creative and digital assets worldwide. The work blends enterprise software engineering with machine learning and generative AI to enable intelligent search, semantic understanding, auto-tagging, multimodal indexing, and AI-driven automation. This is a mission-critical, high-scale systems role used daily by cross-functional teams.

Responsibilities

• Architect and build high-throughput, low-latency microservices and ingestion pipelines using Java and modern distributed architectures

• Develop and integrate enterprise Digital Asset Management solutions (e.g., Nuxeo, Orange Logic, or open-source frameworks) by customizing asset models, lifecycle workflows, and storage abstractions

• Apply ML and generative AI to digital assets for natural language search, semantic/vector search, automated tagging, image/video understanding, captioning, transcripts, summaries, metadata enrichment, and generative content workflows

• Ensure high availability, data consistency, and fault tolerance across distributed storage tiers, caching layers, and search engines at petabyte-scale

• Collaborate end-to-end with cross-functional teams, including CI/CD, containerized deployments (Kubernetes/Docker), and observability (metrics, logs, traces)

• Convert ambiguous requirements into clean, testable, well-documented technical specifications and APIs

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience

• 3+ years of professional software engineering experience focused on backend systems

• Strong proficiency in Java (modern Java features, concurrency, performance profiling, Spring Boot)

• Practical experience with RESTful APIs and/or event-driven architectures or distributed streaming systems (e.g., Apache Kafka)

• Familiarity with relational databases (e.g., PostgreSQL) and search/vector stores (e.g., Elasticsearch, OpenSearch, Milvus, Pinecone)

Benefits

• Shape mission-critical DAM platforms used daily by cross-functional teams

• Work at the intersection of distributed backend engineering and ML/generative AI for intelligent asset workflows

• Collaborative environment with product, ML, platform architects, and downstream engineering teams