decagon

Senior/Staff Software Engineer, Data Lifecycle

Listed by employer · Checked

Posted within 60 days ·

  • onsite
  • FullTime
  • Engineering
  • New York City
Work arrangement
onsite
Employment
FullTime
Stated compensation
USD 200,000–400,000 1 YEAR
Apply on company website ↗
01 / A QUICK CHECK BEFORE YOU APPLY

Does the location policy fit?

Choose where you would work from. We’ll compare it with the posting’s stated requirements.

Choose the country you will work from. You can change this anytime.

Country and sponsorship changes take effect when you click Check eligibility.

Applying from Iran

Stated requirements conflict with your selections

Checked for applicants in Iran; employer sponsorship is not needed. Based on the source posting · not a hiring or work-authorization guarantee.

Your country is outside the stated applicant locations.

Why this result?

1 stated blockers

  • Your country is outside the stated applicant locations.

2 still unclear

  • Office attendance is required. Relocation and work permission have not been assessed.
  • Visa sponsorship is not specified.
Source: ashbyChecked Original posting ↗

Requirements

2 with evidence7 unclear or unstated
Remote policy
onsite
“Provider workplace type: onsite”
From employer posting metadata
Geographic scope
US
“Final compensation may vary based on location within the United States.”
See matched passage in original description ↓
Employment type
FullTime
Compensation
USD 200,000–400,000 1 YEAR
7 fields not stated in this posting
Employer sponsorship
Not specified
Degree requirement
Not specified
Security clearance
Not mentioned
Timezone / hours
Not specified
Citizenship requirement
Not mentioned
Minimum experience (years)
Not specified
Work authorization
Not specified

These details were not stated in the tracked posting. Confirm with the employer.

READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

Reading view uses normalized posting text so exact evidence excerpts can be highlighted.

About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.
Read full descriptionShow less description
We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Data Lifecycle at Decagon builds the systems that govern how sensitive customer data is handled throughout its lifetime: what we store, who can access it, how we redact it, and when we delete it. We turn complex privacy requirements into reliable infrastructure and product that customers can configure and trust. This team is core to how Decagon scales. Our AI agents work with sensitive information across conversations, tool calls, and customer systems. The frameworks we build need to protect that data consistently across the platform, while preserving the context customers need to operate and improve their agents. A failure mode we debug in production becomes a guardrail, a test, or a piece of tooling that catches it everywhere. Our systems run for companies like Hertz, American Airlines, and Notion across chat, voice, email, and SMS. About the Role You’ll design and build the platform infrastructure that let customers control how their data is collected, retained, redacted, and deleted. That means strong engineering underneath, and clear abstractions on top that hold up across different enterprise requirements without forking per customer. You’ll work day to day with product management, governance, and security: understanding customer requirements, defining data handling guarantees, reviewing designs, and iterating through launch. You’ll stay close enough to customers to understand their privacy and operational needs in depth and to ensure what you’re building is actually right for them. Engineers here own features end to end, from technical architecture through deployment and the iteration after it. On this team, that includes verifying that sensitive data is protected and the action actually completes. An understanding of durable and fault-tolerant systems is key. 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, CCPA, or PCI, and translating them into engineering controls Background with LLMs, evals, or AI agent systems, especially handling sensitive data in model inputs, outputs, and traces Experience with observability, audit trails, or operational tooling for large-scale data systems Work with sensitive data in voice, images, or other non-text formats Compensation $200K – $400K + Offers Equity This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact. In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States. Benefits We proudly offer the following benefits for our full-time employees: Medical, Dental, and Vision benefits for you and your family Life Insurance and Disability Benefits Retirement Plan (e.g., 401K, pension) Parental Leave Fertility and family building benefits through Carrot Monthly stipend to support your wellness, lifestyle, and work-life balance Daily lunches and snacks in the office to keep you at your best Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Original formatting and links

About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.

Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.

We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.

About the Team

Data Lifecycle at Decagon builds the systems that govern how sensitive customer data is handled throughout its lifetime: what we store, who can access it, how we redact it, and when we delete it. We turn complex privacy requirements into reliable infrastructure and product that customers can configure and trust.

This team is core to how Decagon scales. Our AI agents work with sensitive information across conversations, tool calls, and customer systems. The frameworks we build need to protect that data consistently across the platform, while preserving the context customers need to operate and improve their agents. A failure mode we debug in production becomes a guardrail, a test, or a piece of tooling that catches it everywhere.

Our systems run for companies like Hertz, American Airlines, and Notion across chat, voice, email, and SMS.

About the Role

You’ll design and build the platform infrastructure that let customers control how their data is collected, retained, redacted, and deleted. That means strong engineering underneath, and clear abstractions on top that hold up across different enterprise requirements without forking per customer.

You’ll work day to day with product management, governance, and security: understanding customer requirements, defining data handling guarantees, reviewing designs, and iterating through launch. You’ll stay close enough to customers to understand their privacy and operational needs in depth and to ensure what you’re building is actually right for them.

Engineers here own features end to end, from technical architecture through deployment and the iteration after it. On this team, that includes verifying that sensitive data is protected and the action actually completes. An understanding of durable and fault-tolerant systems is key.

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, CCPA, or PCI, and translating them into engineering controls

  • Background with LLMs, evals, or AI agent systems, especially handling sensitive data in model inputs, outputs, and traces

  • Experience with observability, audit trails, or operational tooling for large-scale data systems

  • Work with sensitive data in voice, images, or other non-text formats

Compensation

$200K – $400K + Offers Equity

This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact.

In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States.

Benefits

We proudly offer the following benefits for our full-time employees:

  • Medical, Dental, and Vision benefits for you and your family

  • Life Insurance and Disability Benefits

  • Retirement Plan (e.g., 401K, pension)

  • Parental Leave

  • Fertility and family building benefits through Carrot

  • Monthly stipend to support your wellness, lifestyle, and work-life balance

  • Daily lunches and snacks in the office to keep you at your best

  • Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)

These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

Matched by role category. Review each posting’s requirements before applying.

Explore stated remote geography

These collections reflect applicant location statements, not authorization or citizenship.

THE JOB ELIGIBILITY CHECKER

Check a job