This is a remote position. We are recruiting two Senior Software Engineers with deep Avid MAM experience to support a long term, high impact media archive migration program for a major global news and media organization. The program focuses on modernizing legacy Avid based archive systems and migrating media assets, metadata, and workflows into a modern cloud native MAM and storage environment.
This role is best suited to engineers who enjoy working close to media systems, metadata, and real world broadcast workflows, rather than pure infrastructure or DevOps focused work.
Program Context: The program is migrating large scale news and archive content from a legacy environment built on Avid MAM, DIVA archive, and object storage into a modern MAM platform and Google Cloud Storage. The focus is on metadata integrity, accurate media linkage, successful ingest, and long term operational readiness. You will play a key role in ensuring that complex Avid metadata, AXF packages, and media objects are correctly analyzed, transformed, validated, and ingested into the new platform with zero data loss.
Avid MAM and AXF metadata engineering.
Analyze and process Avid AXF exports for assignments, stories, clips, and media objects.
Extract, validate, and troubleshoot metadata using Python-based tooling.
Understand and work with Avid project hierarchies, relationships, and legacy metadata structures.
Retrieve and validate media object locations via archive APIs.
Identify and resolve corrupted exports, inconsistencies, and legacy formatting issues.
Metadata transformation and MAM ingest.
Design and implement transformation workflows to convert Avid metadata into flat, normalized JSON.
Map Avid fields to target MAM schemas and ingest specifications.
Generate and validate MAM compliant sidecar JSON files.
Support end to end ingest testing and verify correct asset representation and proxy generation.
Media validation and migration readiness.
Validate media completeness across Avid, archive systems, and object storage.
Perform checksum verification, object existence checks, and readiness validation.
Support preparation of migration manifests for bulk transfer workflows.
Identify and resolve mismatches between metadata and physical media.
Python workflow engineering.
Enhance Python workflows used for metadata extraction, transformation, and orchestration.
Implement robust error handling, detailed logging, and recoverable execution paths.
Optimize pipelines for high volume archival workloads.
Collaborate closely with technical stakeholders to validate logic and improve tooling.
Ingest verification and documentation.
Verify successful migration and ingest into the new MAM and cloud storage.
Confirm metadata accuracy, media presence, and correct asset linkage.
Produce detailed documentation, workflow diagrams, and operational runbooks.
Contribute to testing cycles, validation reviews, and regular status reporting.
Strong hands on experience with Avid MAM, this is mandatory.
Deep understanding of Avid metadata structures, AXF packaging, and assignment story relationships.
Experience working with archive systems and media object validation.
Strong Python engineering skills for metadata processing and workflow automation.
Experience working with JSON based schemas and transformation logic.
Solid understanding of object storage workflows, including AWS S3 and Google Cloud Storage.
Ability to diagnose complex data and metadata issues across multiple systems.
Experience on large scale media or news archive migrations.
Background working in broadcast or news media environments.
Familiarity with modern MAM ingest workflows and proxy generation.
Experience producing runbooks and documentation for operational teams.
This is a rare opportunity to join a long-running, well-scoped media transformation program where Avid expertise and engineering depth are genuinely critical. You will be working on complex, meaningful systems that underpin modern news and media operations, with a competitive market rate and long term contract stability.
Duration: 12 months
Rate: $40-$45/hr
Location: LATAM preferred, US based candidates also considered
Type: Contract