Decagon Logo

Decagon

Senior/Staff Software Engineer, Data Lifecycle

Posted 9 Days Ago
Be an Early Applicant
In-Office
New York City, NY, USA
200K-400K Annually
Senior level
In-Office
New York City, NY, USA
200K-400K Annually
Senior level
Build data lifecycle infrastructure for collecting, retaining, redacting, and deleting sensitive customer data. Responsibilities include PII and PHI detection, configurable retention policies, reliable deletion workflows, self-service APIs, LLM-backed anomaly detection, multimodal redaction, monitoring, auditability, and fault-tolerant systems at scale.
The summary above was generated by AI

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.

Similar Jobs

Yesterday
In-Office or Remote
New York, NY, United States
180K-200K Annually
Senior level
180K-200K Annually
Senior level
Healthtech • Telehealth
Leads and develops a data engineering team responsible for Snowflake, dbt, Python services on AWS, Airflow orchestration, integrations, reliability, and CI/CD. Owns technical strategy, platform administration, access controls, cost management, incident response, engineering standards, delivery, and team development. Partners with product, analytics engineering, DevOps, and business stakeholders to build scalable, reliable data systems.
Top Skills: Amazon EcsApache AirflowAWSAws LambdaCi/CdDbtFivetranPythonSnowflakeSQLTerraform
Yesterday
Hybrid
New York, NY, USA
80K-100K Annually
Junior
80K-100K Annually
Junior
AdTech • Big Data • Digital Media • Software
Build and maintain automation systems, backend services, and lightweight internal web applications. Analyze cross-functional workflows, identify automation opportunities, and implement scalable solutions. Collaborate with engineering, product, operations, and sales teams while using AI-assisted development tools and LLM integrations. Participate in code reviews and continuous improvement while developing software engineering fundamentals.
Top Skills: AirflowAWSCursorDockerJavaJavaScriptModel Context ProtocolNext.JsNode.jsOpenaiPostgresPythonReactTypescript
Yesterday
Remote or Hybrid
2 Locations
69K-114K Annually
Entry level
69K-114K Annually
Entry level
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Supports Pfizer CentreOne’s inside sales and marketing activities by reviewing and routing marketing-qualified leads, executing outreach sequences, documenting activity in Salesforce, and assisting with campaigns, content, meetings, reporting, and marketing projects. The role develops commercial expertise across marketing, inside sales, and business development while progressing leads toward initial meetings and BD handoff.
Top Skills: HubspotExcelMicrosoft OutlookMicrosoft PowerpointMicrosoft SharepointMicrosoft TeamsMicrosoft WordSalesforce

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account