Streaming & Media Pipeline Engineer, LSO Playout

Position summary

LSO Media Group is seeking a Streaming & Media Pipeline Engineer to develop the media processing and delivery components of LSO Playout. This full-time position reports to the Director of Product & Engineering, LSO Playout. The forthcoming product is planned to offer cloud-only and local-and-cloud options for scheduled channels. You will help determine how uploaded media becomes ready to play and how channel output reaches streaming destinations with consistent quality, observable failures and understandable resource requirements.

Your work will connect the scheduler, media store and output paths, covering asset inspection, normalization, encoding, packaging and contribution monitoring. You will assess build-versus-service decisions with platform colleagues and document the latency, quality, reliability and cost tradeoffs. The role requires practical experience diagnosing real media failures and verifying end-to-end playback. AI-assisted development is encouraged, with engineers expected to inspect generated commands and code, test representative content and remain accountable for production behavior.

Responsibilities

• Design media ingest and inspection workflows that identify file properties, corrupt or incomplete assets and conditions that prevent safe scheduling.
• Build repeatable transcode and normalization jobs with validation, retries, progress reporting and clear readiness states for the channel engine.
• Implement and evaluate encoding and packaging paths, including HLS where appropriate, against agreed playback, latency and resource targets.
• Integrate selected contribution and streaming destinations, documenting supported protocols, authentication requirements and reconnect behavior.
• Preserve and validate required audio tracks, captions and metadata through supported processing paths, making unsupported combinations visible.
• Instrument media processing and channel output for dropped frames, stalls, discontinuities, errors and other agreed quality indicators.
• Work with platform engineers to estimate compute, storage and delivery costs and to test capacity under representative channel and asset workloads.
• Develop end-to-end playback tests across selected clients and failure scenarios, using representative media and repeatable signal checks.
• Use AI tools to accelerate development and troubleshooting while reviewing generated processing commands, validating outputs and protecting confidential media.
• Document processing profiles, operational limits and recovery procedures, and help diagnose delivery incidents as support arrangements develop.

Required qualifications

• At least four years of software engineering experience, including hands-on development of video processing or streaming systems.
• Practical experience with encoding, transcoding and media inspection using tools or frameworks such as FFmpeg, GStreamer or equivalent systems.
• Understanding of streaming fundamentals, including manifests, segments, timestamps, buffering, audio/video synchronization and network interruptions.
• Experience building observable processing jobs or services with durable state, retries, automated tests and useful operational diagnostics.
• Ability to use AI coding and analysis tools while independently reviewing code and validating resulting media quality, correctness and performance.
• A degree in computer science, engineering or a related field, or equivalent practical experience, with clear written communication and cross-team collaboration skills.

Preferred qualifications

• Experience operating continuous live channels or integrating contribution protocols such as SRT or RTMP.
• Experience with caption processing, loudness workflows, adaptive bitrate delivery or objective media-quality measurements.
• Experience comparing managed media services with self-hosted processing and evaluating their capacity and cost characteristics.

Measures of success

• Representative assets move through an observable preparation workflow with accurate readiness and failure states.
• A reference streaming channel plays continuously within agreed quality and latency targets under defined test conditions.
• Processing and delivery failures can be detected and investigated using evidence that identifies the affected asset, channel and stage.
• Architecture recommendations include measured quality, capacity and cost assumptions that support product decisions.

First 90 days

During your first 90 days, you will assemble a representative media test set, document processing and delivery requirements, and build an ingest-to-stream prototype. You will measure quality, latency and resource use, exercise selected interruption scenarios and identify limits affecting supported formats or destinations. With the director and platform team, you will recommend initial processing profiles, service boundaries and monitoring priorities, supported by test results and a practical cost model.

Compensation

Proposed annual base salary of $135,000–$180,000 USD. The final offer will reflect relevant experience, qualifications and the agreed scope of the position, subject to approval. This range covers base pay only; any incentive compensation or benefits would be specified separately in an employment offer.

What to include in your application

If available, include a nonconfidential streaming or media-processing project and explain your contribution, tradeoffs and validation methods. Show how AI tools helped your work and how you checked the output. Do not submit media you lack permission to share.