Project Based Recruitment | Software / Platform / Data Engineer - Agent Trace Collection | $100/Hour | Remote
This project focuses on building an end-to-end AI agent trace collection and data pipeline designed to capture GitHub Copilot CLI agent traces from developer environments, securely process the data in Azure, remove sensitive information, and deliver a sanitized dataset for technical review.
The project is particularly suitable for engineers who can independently turn a technical design into a production-ready implementation while treating data privacy, cloud security, and sensitive-data protection as core engineering requirements.
If you are actively looking for remote wfa jobs, this project may be worth reviewing quickly because the engagement has a near-term expected start date.
Job Information
Position: Software / Platform / Data Engineer – Agent Trace Collection
Project Type: Project-Based Contractor
Work Arrangement: Remote
Compensation: $100/hour
Minimum Commitment: 20 hours per week
Daily Commitment: At least 4 hours per day
Time Zone Overlap: 4 hours with PST
Contract Duration: 3 months
Expected Start: Next week
Location Requirement: North America
Interview: One approximately 30-minute technical and cultural discussion
Registration Link: REGISTRATION LINK HERE
What You Will Work On
The selected engineer will own the technical implementation across the entire trace collection pipeline.
The project includes setting up an OpenTelemetry-based capture system on developer machines, configuring endpoint environment variables and Bash profiles, exporting telemetry through OTLP, and building the collector pipeline using receivers, processors, and exporters.
Another major responsibility is developing the central Azure ingestion and privacy-processing layer. This includes detecting and removing PII, secrets, credentials, and other sensitive information before traces become available to reviewers.
The project also involves connecting sanitized data stores and developing a read-only trace viewer that allows technical teams to correlate tasks, sessions, and individual traces.
This is not simply a monitoring configuration role. The engineer is expected to build and connect the components into a functioning production-oriented system.
Key Responsibilities
Build an OpenTelemetry capture path for developer environments.
Configure OTLP-based trace export.
Develop and manage OpenTelemetry collector pipelines.
Implement receivers, processors, and exporters.
Build the central ingestion pipeline in Azure.
Develop privacy scrubbing for PII and sensitive secrets.
Apply techniques such as regex detection, entropy analysis, redaction, and tokenization.
Connect sanitized trace data to appropriate storage systems.
Build a read-only trace viewer.
Implement task-to-session-to-trace correlation.
Apply cloud security fundamentals throughout the architecture.
Maintain appropriate RBAC, private networking, and audit controls.
Required Technical Skills
Candidates should have strong production engineering experience and be comfortable working independently.
Key requirements include:
5+ years of software, platform, or data engineering experience.
3+ years of hands-on Azure experience or comparable major-cloud experience.
2+ years working with observability or telemetry pipelines.
Direct OpenTelemetry experience.
Strong understanding of OTLP, collectors, spans, traces, and semantic conventions.
Solid Python or Node.js development skills.
Bash scripting experience.
Practical experience with data privacy and PII protection.
Experience detecting and removing secrets from data.
Understanding of cloud security, RBAC, private networking, and auditing.
Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
Azure Experience
Experience with Azure PaaS technologies is particularly important for this project.
Relevant technologies include:
Azure Container Apps or AKS
Azure API Management
Azure Data Explorer (ADX) / Kusto
Application Insights
Azure Data Lake Storage Gen2
Azure Blob Storage
Azure Key Vault
Microsoft Entra ID
Engineers coming from another major cloud environment may also be considered when their experience can transfer effectively to Azure PaaS.
Nice-to-Have Experience
Additional experience that can strengthen an application includes:
Grafana
Telemetry backend implementation
LLM agent observability
Generative AI infrastructure
Cross-cloud identity federation
Azure AD / Entra ID and GCP IAM integration
Who Should Apply?
This project is a strong match for engineers who have worked across multiple areas rather than focusing on only one narrow technology.
You may be a good fit if your background includes platform engineering, cloud engineering, data engineering, observability, DevOps, SRE, backend development, or AI infrastructure and you are comfortable owning a technical system from implementation through delivery.
The ideal candidate should be able to work independently from a written technical design and deliver a functional pipeline with minimal supervision.
Privacy is also a major consideration. Experience handling sensitive telemetry, PII, secrets, credentials, or other protected data will be especially valuable.
Compensation and Commitment
The project offers a compensation rate of $100 per hour.
The expected commitment is:
Minimum 4 hours per day
Minimum 20 hours per week
4 hours of working-time overlap with PST
Approximately 3 months
Remote contractor engagement
Because the expected start date is next week, qualified engineers who are interested should consider registering as soon as possible rather than waiting until the project is fully filled.
Registration
Interested candidates can submit their registration through the designated application link below.
Registration Link: REGISTRATION LINK HERE
Please review the technical requirements carefully before applying, particularly the Azure, OpenTelemetry, Python/Node.js, and privacy-scrubbing requirements.
Why This Project Stands Out
This project combines several areas that are becoming increasingly important in modern AI infrastructure: cloud engineering, observability, telemetry pipelines, developer tooling, data privacy, and AI agent systems.
Rather than contributing to only one isolated component, the selected engineer will work across the complete technical flow—from endpoint trace collection through centralized processing, privacy scrubbing, storage, and visualization.
For engineers looking for project-based work that combines cloud infrastructure and AI engineering, this represents an opportunity to work on a technically demanding system with practical applications in next-generation AI development.
Final Note
Project-based engineering opportunities with strong Azure, OpenTelemetry, and AI infrastructure requirements can be highly competitive, particularly when the engagement has a near-term start date.
If your experience matches the requirements and you are available for at least 20 hours per week, it is worth preparing your application now.
Registration Link: REGISTRATION LINK HERE
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