Video Workflow Automation Engineer

Leidos is seeking a Video Workflow Automation Engineer in support of the AEGIS Enterprise Video Services team. This role is responsible for software development, with a focus on creating efficient and scalable video workflows. This role will design, develop, and maintain code that automates various aspects of video distribution, streamlining processes and accelerating delivery times. 

This position requires the ability to work independently with general direction. Join us at AEGIS where the sky is NOT the limit!

Key Responsibilities

• Workflow Development: Design, develop, and maintain software solutions that automate video distribution workflows, including encoding, transcoding, packaging, and delivery.
• Automation: Implement automated processes to reduce manual intervention and streamline operations, such as background tasks, batch processing, and error handling.
• Optimization: Identify and implement performance optimizations to improve video delivery speed and efficiency.
• Integration: Integrate video workflows with existing systems and platforms, such as content management systems, delivery networks, and analytics tools.
• Problem-Solving: Troubleshoot and resolve technical issues related to video workflows and automation.
• Collaboration: Work closely with other team members, including product managers, designers, and quality assurance engineers, to ensure successful project delivery.
• Content-Aware Encoding Scripts: Develop and maintain AI-assisted Python and Bash scripts to dynamically adjust FFmpeg parameters for HEVC/H.265 and H.264 codecs based on real-time content complexity analysis.
• Intelligent Transport Routing: Write automated scripts to monitor SRT transport protocol health, utilizing machine learning models to predict packet loss and automatically trigger failovers or route bandwidth to third-party CDNs during high-traffic live events.
• 4K HDR Workflow Automation: Implement AI scripts to automate color space conversions and metadata tagging for 4K HDR live streams, ensuring seamless handoffs between ground hardware and cloud infrastructure.
• Perceptual Quality Monitoring: Integrate AI-driven telemetry scripts with VMAF (Video Multi-method Assessment Fusion) to establish automated baseline grading for live streams, triggering alerts when perceptual video quality dips below acceptable broadcast thresholds.
• Anomaly Detection: Deploy machine learning scripts to continuously parse system logs from UHD video routers and edge encoders, identifying predictive hardware failures or stream degradation before they impact the live feed.
• Cloud Playout Automation: Author API-driven scripts to automate the spin-up and teardown of cloud-based Master Control Rooms, optimizing compute resources and ensuring cost avoidance during non-peak hours.
• Smart SCTE-35 Insertion: Develop AI-assisted logic for the automated insertion of SCTE-35 markers, using computer vision or audio cue recognition to accurately place ad breaks or program boundaries without manual operator intervention.
• Real-Time Audio Restoration: Implement and script AI audio processing tools into the live broadcast chain for dynamic noise suppression, vocal isolation, and automated leveling of field audio.
• Automated Captioning & Metadata: Write integration scripts for AI speech-to-text models to generate highly accurate, low-latency closed captions and descriptive metadata for live VOD packaging.

Basic Qualifications

• Must be able to obtain a Public Trust (US Citizenship required).
• Strong programming skills in languages such as Python, Java, or C++.
• Experience with video encoding and transcoding technologies (e.g., FFmpeg, x264, H.265).
• Knowledge of video streaming protocols (e.g., HTTP Live Streaming, DASH).
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and cloud-native technologies.
• Excellent problem-solving and analytical skills.
• Ability to work independently and as part of a team.

Preferred Qualifications

• Experience with various AI platforms and integration with video streaming technology.
• Experience with video delivery networks (CDNs) and their APIs.
• Knowledge of video analytics tools and metrics.
• Experience with containerization technologies (e.g., Docker, Kubernetes).
• Experience with scripting languages (e.g., Bash, PowerShell).

Education

Bachelor’s degree in computer science, Engineering, or a related field.

2-4 years of experience in software development, with a focus on video workflows and automation.

AppMod

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:

May 15, 2026

Pay Range:

Pay Range $69,550.00 - $125,725.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.