Senior/Staff Software Engineer, Data Lifecycle

Decagon; Myrtle Point (OR); On-site; USD 120,000 - 170,000; Full time

Job summary

Decagon in Oregon is seeking a senior software engineer focused on data privacy, redaction, and lifecycle governance. You will build PII handling systems, design retention policies, and create reliable data deletion workflows across storage and derived data.

You will also develop self-serve tools and APIs for customers to configure and understand their data lifecycle, and collaborate on LLM-backed systems that detect anomalies and enforce safety across conversations, attachments, and other data.

Qualifications

• 4+ years building software products with strong product thinking.
• Proficient in Python and comfortable across the full stack.
• Experience designing backend systems and data pipelines with retries and failure recovery.
• Understanding of operational maturity including observability and monitoring.
• Ability to reason about data flows, copies, and failure points in complex systems.
• Strong debugging skills for deep technology stacks and rapid issue resolution.
• Judgment about when to ship fast vs. privacy and safety considerations.

Responsibilities

• Build PII handling and redaction systems across conversations, agent traces, and customer data.
• Design configuration abstractions for redaction and retention policies with safe defaults.
• Create reliable data deletion workflows across storage systems and derived data.
• Develop self-serve tools and APIs for customers to configure and test their data lifecycle policies.
• Build LLM-backed systems that scan for data anomalies and violations.
• Train and/or tune models for detecting data forms (PII, PHI).
• Extend redaction and identification to multimodal agents (images, attachments, voice notes, documents).
• Implement monitoring and auditability to show data processed, remaining data, and policy failures without exposing secrets.
• Handle data lifecycle at scale including backfills, partial failures, and safe rollouts across Fortune 100 environments.

Skills

Python

Backend systems

Data pipelines

Observability

Debugging

Product thinking

System reliability

Job description

In this role, you will

• Build PII handling and redaction systems that identify and protect sensitive information across conversations, agent traces, and other customer data
• Design configuration abstractions for redaction and retention policies that balance enterprise flexibility with clear, safe defaults
• Build reliable data deletion workflows that propagate across storage systems and derived data, with retries, verification, and visibility into failures
• Build self-serve tools and APIs that let customers configure, test, and understand their data lifecycle policies without relying on an engineer
• Build LLM-backed systems that scan and detect data anomalies and violations
• Train and/or tune models for detecting data of various forms (including PII and PHI)
• Extend redaction and identification to multimodal agents, including images, attachments, voice notes, and documents.
• Build monitoring and auditability that make it clear what data was processed, what remains, and where a policy has failed—without exposing sensitive information in the process
• Handle data lifecycle systems at scale, including backfills, partial failures, and safe rollouts; your work will touch critical flows for Fortune 100 companies

Your background and skillset look something like this

• 4+ years building software products, with strong product thinking
• Proficient in Python, comfortable working across the entire stack
• Experience designing reliable backend systems and data pipelines, including asynchronous processing, retries, and failure recovery
• Understanding of what operational maturity looks like for critical systems, including observability and monitoring
• Complex systems instincts: you can reason about where data flows, where copies persist, and what happens when one part of a workflow fails
• A high degree of comfort debugging system failures in deep technology stacks, using whatever tool gets you to the answer
• Judgment about when to ship fast and when correctness, privacy, and irreversible operations require slowing down

Even better

• Experience with PII detection, redaction, tokenization, or secure handling of sensitive data
• Experience building data retention, deletion, or privacy request workflows across multiple storage systems
• Experience building security-sensitive product systems, such as authentication, authorization, and data access controls
• Familiarity with privacy and compliance requirements such as GDPR,