Engineering Lead - AI - Driven MAM

Experience: 6 + years
Expected Notice Period: 15 Days Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Remote,New Delhi,Bengaluru,Mumbai Technical Lead

What youll own

Leading the re-architecture of Zooms database foundation with a focus on scalability, query performance, and vector-based search support

Replacing or refactoring our current in-house object store and metadata database to a modern, high-performance elastic solution

Collaborating closely with our core platform engineers and AI/search teams to ensure seamless integration and zero disruption to existing media workflows

Designing an extensible system that supports object-style relationships across millions of assets, including LLM-generated digital asset summaries, time-coded video metadata, AI generated tags, and semantic vectors

Driving end-to-end implementation: schema design, migration tooling, performance benchmarking, and production rolloutall with aggressive timelines

Skills & Experience We Expect

Were looking for candidates with 7-10 years of hands-on engineering experience, including 3+ years in a technical leadership role. Your experience should span the following core areas:

System Design & Architecture

(3-4 yrs)

Strong hands-on experience with the Java/JVM stack (GC tuning), Python in production environments

Led system-level design for scalable, modular AWS microservices architectures

Designed high-throughput, low-latency media pipelines capable of scaling to billions of media records

Familiar with multitenant SaaS patterns, service decomposition, and elastic scale-out/in models

Deep understanding of infrastructure observability, failure handling, and graceful degradation

Database & Metadata Layer Design

(3-5 yrs)

Experience redesigning or implementing object-style metadata stores used in MAM/DAM systems

Strong grasp of schema-less models for asset relationships, time-coded metadata, and versioned updates

Practical experience with DynamoDB, Aurora, PostgreSQL, or similar high-scale databases

Comfortable evaluating trade-offs between memory, query latency, and write throughput

Semantic Search & Vectors

(1-3 yrs)

Implemented vector search using systems like Weaviate, Pinecone, Qdrant, or Faiss

Able to design hybrid (structured + semantic) search pipelines for similarity and natural language use cases

Experience tuning vector indexers for performance, memory footprint, and recall

Familiar with the basics of embedding generation pipelines and how they are used for semantic search and similarity-based retrieval

Worked with MLOps teams to deploy ML inference services (e.g., FastAPI/Docker + GPU-based EC2 or SageMaker endpoints)

Understands the limitations of recognition models (e.g., OCR, face/object detection, logo recognition), even if not directly building them

Media Asset Workflow

(2-4 yrs)

Deep familiarity with broadcast and OTT formats: MXF, IMF, DNxHD, ProRes, H.264, HEVC

Understanding of proxy workflows in video post-production

Experience with digital asset lifecycle: ingest, AI metadata enrichment, media transformation, S3 cloud archiving

Hands-on experience working with time-coded metadata (e.g., subtitles, AI tags, shot changes) management in media archives

Cloud-Native Architecture (AWS)

(3-5 yrs)

Strong hands-on experience with ECS, Fargate, Lambda, S3, DynamoDB, Aurora, SQS, EventBridge

Experience building serverless or service-based compute models for elastic scaling

Familiarity with managing multi-region deployments, failover, and IAM configuration

Built cloud-native CI/CD deployment pipelines with event-driven microservices and queue-based workflows

Frontend Collaboration & React App Integration

(2-3 yrs)

Worked closely with React-based frontend teams, especially on desktop-style web applications

Familiar with component-based design systems, REST/GraphQL API integration, and optimizing media-heavy UI workflows

Able to guide frontend teams on data modeling, caching, and efficient rendering of large asset libraries

Experience with Electron for desktop apps