Software / Platform / Data Engineer — Agent Trace Collection
Company: Turing · Pay: $100/hr · Location: Remote — North America · Type: contractor · Posted: 2026-09-19
Architect end-to-end data pipelines, enforce enterprise privacy standards, and shape frontier AI agent benchmarks with Turing.
About Turing
Turing stands at the forefront of the global artificial general intelligence (AGI) infrastructure movement. By collaborating directly with premier frontier AI research labs, Turing accelerates next-generation model development through high-grade training data, meticulous behavioral evaluations, and elite engineering talent. For senior engineers looking to engage with cutting-edge artificial intelligence projects, Turing provides unparalleled access to high-impact remote assignments.
About the Role
This high-visibility engagement challenges an experienced engineer to build the technical implementation of an advanced tracing system. Specifically, you will capture GitHub Copilot CLI agent traces across developer machines, centralize privacy scrubbing within Azure, and serve a fully sanitized, queryable dataset for review. You will own the pipeline end-to-end—from the endpoint capture script to Azure ingestion, scrubbing, and viewer visualization.
Are You a Fit?
You are an ideal match for this role if you can take a comprehensive written design and ship a fully functional production pipeline mostly on your own. Crucially, you treat data privacy as a hard, uncompromising requirement rather than an afterthought.
What Your Day-to-Day Looks Like
- OpenTelemetry Capture Path: Stand up endpoint environment variables, `.bashrc` setups, OTLP exports, and complete collector pipelines (receivers to processors to exporters).
- Central Ingestion & Privacy Scrubbing: Build the central ingestion and PII/secret detection-and-redaction block in Azure before any data ever reaches human reviewers.
- Sanitized Stores & Trace Viewer: Wire up secure sanitized data stores and a read-only trace viewer featuring seamless task-to-session-to-trace correlation.
Required Skills & Experience
- Education: Bachelor’s degree in Computer Science, Engineering, or a related field—or equivalent practical experience.
- Engineering Tenure: 5+ years of professional experience in software, platform, or data engineering, successfully shipping production systems.
- Cloud & Observability: 3+ years hands-on with Azure (or a comparable major cloud with clear transfer to Azure PaaS), including 2+ years building observability or telemetry pipelines with direct OpenTelemetry experience (OTLP, collectors, spans/traces, semantic conventions).
- Azure PaaS Stack: Proficiency with Container Apps/AKS, API Management, ADX/Kusto or App Insights, ADLS Gen2/Blob, Key Vault, and Entra ID.
- Programming & Scripting: Solid background in Python or Node.js, combined with robust Bash scripting capabilities.
- Data Privacy & Security: Practical background in PII and secret scrubbing (using regex, entropy analysis, and tokenization), alongside core cloud security and data pipeline fundamentals (RBAC, private networking, audit).
Nice-to-Have Qualifications
- Grafana and telemetry-backend setup experience.
- LLM-agent or Generative AI observability exposure.
- Cross-cloud identity federation expertise (Azure AD/Entra ID ⇄ GCP IAM).
Engagement Details
- Compensation: $100 per hour.
- Commitment Requirements: At least 4 hours per day and a minimum of 20 hours per week, with a mandatory 4-hour overlap with Pacific Standard Time (PST).
- Employment Type: Contractor assignment (no medical benefits or paid leave).
- Contract Duration: 3 months, with an expected start date slated for next week.
- Location: North America (Remote).
Perks of Freelancing With Turing
- Work in a fully flexible, remote environment from anywhere in North America.
- Directly collaborate on cutting-edge AI projects with leading LLM and frontier technology companies.
- Accelerate your technical career by tackling complex engineering challenges at the frontier of AGI.
Interview & Evaluation Process
The evaluation process is streamlined and efficient, lasting approximately 30 minutes. It consists of a single interview round focusing on both technical depth and cultural alignment, ensuring you can quickly transition into the project starting next week.
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Responsibilities
- OpenTelemetry Capture Path: Stand up endpoint environment variables, `.bashrc` setups, OTLP exports, and complete collector pipelines (receivers to processors to exporters).
- Central Ingestion & Privacy Scrubbing: Build the central ingestion and PII/secret detection-and-redaction block in Azure before any data ever reaches human reviewers.
- Sanitized Stores & Trace Viewer: Wire up secure sanitized data stores and a read-only trace viewer featuring seamless task-to-session-to-trace correlation.
Qualifications
- Grafana and telemetry-backend setup experience.
- LLM-agent or Generative AI observability exposure.
- Cross-cloud identity federation expertise (Azure AD/Entra ID ⇄ GCP IAM).
Skills
- Education: Bachelor’s degree in Computer Science, Engineering, or a related field—or equivalent practical experience.
- Engineering Tenure: 5+ years of professional experience in software, platform, or data engineering, successfully shipping production systems.
- Cloud & Observability: 3+ years hands-on with Azure (or a comparable major cloud with clear transfer to Azure PaaS), including 2+ years building observability or telemetry pipelines with direct OpenTelemetry experience (OTLP, collectors, spans/traces, semantic conventions).
- Azure PaaS Stack: Proficiency with Container Apps/AKS, API Management, ADX/Kusto or App Insights, ADLS Gen2/Blob, Key Vault, and Entra ID.
- Programming & Scripting: Solid background in Python or Node.js, combined with robust Bash scripting capabilities.
- Data Privacy & Security: Practical background in PII and secret scrubbing (using regex, entropy analysis, and tokenization), alongside core cloud security and data pipeline fundamentals (RBAC, private networking, audit).