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Early Window: Closes in
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Senior Software Engineer

  • Hybrid
  • 6+ years

Salary

$145,000/ year

AI summary

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Description

Join us at the company, where we're on a mission to power exceptional service for every person on the planet. We're accelerating that ambition by building products rooted in AI, automation, and intelligent customer experiences, because behind every interaction lies an opportunity to make a human connection. We’re seeking a Senior Backend Engineer to own the data layer that powers the company’s AI products. In this role, you’ll build and scale integrations and analytics infrastructure that transform raw support data into trusted automation recommendations — directly enabling customers to reduce support costs and improve customer outcomes.

What you’ll be doing

Design, build, and maintain robust platform connectors (ETL: Client → Extractor → Transformer → Loader) across third‑party systems, handling auth, pagination, rate limits, and schema drift.

Extend and scale the Discover insights engine: clustering topics, detecting knowledge gaps, calculating deflection/opportunity impact, and surfacing automation recommendations.

Build and operate resilient data pipelines: real-time webhooks, incremental sync, reindexing, and metrics aggregation with worker queues.

Design, optimize, and maintain search indices and aggregation pipelines for full-text, vector, and hybrid search at scale.

Solve distributed systems problems around multi-tenant isolation, webhook security, incremental sync correctness, and fault-tolerant processing.

Collaborate with product, ML, and design to turn analytics outputs into reliable, explainable customer-facing metrics and recommendations.

What you bring to the role

Strong backend engineering instincts and ownership mindset; you take systems from prototype to production-grade.

Deep experience building data pipelines or integration platforms with attention to correctness and observability.

Practical knowledge of search and analytics infrastructure powering RAG and retrieval features.

Experience with distributed job processing patterns and worker queue design.

A collaborative approach for working with product, data science, and customer-facing teams to deliver measurable ROI.

Basic qualifications

3+ years professional backend engineering experience, ideally in B2B SaaS.

Proficient in Python and backend frameworks (we use FastAPI).

Production experience with MongoDB, Elasticsearch/OpenSearch, and Redis.

Experience designing and operating distributed job processing (RQ, Celery, or similar).

Preferred qualifications

Experience with ETL/orchestration tools (Dagster, Airflow) and S3-based storage patterns.

Familiarity with NLP pipelines, embeddings, or production RAG systems.

Experience with system design for multi-tenant SaaS and webhook security (HMAC/OAuth).

Prior work on analytics engines that translate metrics into product recommendations.

The US annualized base salary range for this position is $145,000.00-$217,000.00. This position may also be eligible for bonus, benefits, or related incentives. While this range reflects the minimum and maximum value for new hire salaries for the position across all US locations, the offer for the successful candidate for this position will be based on job related capabilities, applicable experience, and other factors such as work location. Please note that the compensation details listed in US role postings reflect the base salary only (or OTE for commissions based roles), and do not include bonus, benefits, or related incentives.

The intelligent heart of customer experience

The company software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.

The company believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many the company offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.

As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.

Where you’d work

Part of the week in the office

You can work from

  • United States

About the company

Company hidden

  • Industry: SaaS

Offices in Austin, United States, United States, San Francisco, United States

Your chances

Still hiring, not crowded yet, and you'd be among the first.

  • 17 checks run
  • 8 good signs
  • 0 red flags

Still hiring?

11 checks

Actively hiring

In its favour4

  • Still on the company's own careers site, checked 1 h agoModerate evidence
  • Found in the last 48 hours, before the big job boardsModerate evidence
  • Specific about the basics: pay, place, level, stack and contract all statedSlight evidence
1 moreFewer
  • States its salary: $145KSlight evidence

How crowded?

6 checks

Low

In its favour4

  • In its Early Window: not on the big job boards yetStrong evidence
  • Senior level: far fewer people qualifySlight evidence
  • Asks for MongoDB, which only 1% of open roles doSlight evidence
1 moreFewer
  • Pays below most similar roles, which thins the crowdSlight evidence

Fits Me

How well does this role fit you?

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Details13 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • Redis
  • MongoDB
  • Elasticsearch
  • RAG
Seniority
Senior
Type
Full-time
Industry
SaaS
Specialty
Backend
Region
United States
Show 7 more factsShow less

Role

Category
Development
Specialty
Backend
Seniority
Senior
Experience
3+ years
Tech stack
  • Python
  • Redis
  • MongoDB
  • Elasticsearch
  • RAG

Location

Work model
Hybrid
Region
United States
Offices
  • Austin, United States
  • United States
  • San Francisco, United States
Remote from
  • United States

Compensation

Salary
$145,000 / year
Pay period
Annual

Employment

Type
Full-time

Company

Industry
SaaS

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