Senior Backend Engineer_Hybrid (NYC)

PulseRise Technologies

$130K — $180K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of backend engineering experience with large-scale systems.
  • Strong proficiency in Python; comfort with learning Go.
  • Experience with distributed systems and microservices architecture.
  • Familiarity with SQL and NoSQL databases for data processing.
  • Startup or small-team experience demonstrating real ownership.

Responsibilities

  • Design and build backend services in Go and Python for enterprise clients.
  • Architect data ingestion and processing pipelines for millions of data points.
  • Maintain APIs that support real-time decision-making for the AI platform.
  • Work with the graph database layer and production graph RAG system.
  • Collaborate with ML/AI engineers to integrate models into workflows.
  • Ensure system reliability and design for performance under high load.
  • Mentor engineers and share best practices as the team grows.

Benefits

  • Hybrid work schedule in NYC.
  • Opportunity to shape the platform's long-term technical strategy.
  • Gain experience working with cutting-edge AI technologies.
  • Be part of a high-impact team in a fast-moving company.
Full Job Description
Dear applicants, please note that applications without salary expectations and an active LinkedIn profile will not be considered.

We are looking for a Senior Backend Engineer to join a fast-moving applied AI and data analytics company as one of their highest-priority hires. The focus is twofold: architecting the platform to sustain significantly increased enterprise usage, and building innovative new features with decisions that hold up for years. This is a DRI (Directly Responsible Individual) role - you will own systems end-to-end, from graph database layer to API infrastructure to data pipelines at scale. The sweet spot is someone senior enough to think architecturally, but still energized by hands-on implementation.

Details

Schedule: Full-time

Location: Hybrid (NYC)

Type of collaboration: Full-time employment

The platform connects an organization's entire data landscape - internal systems, social media trends, industry reports, consumer behavior signals - into a single coherent intelligence layer that surfaces insights and automates workflows that used to take analysts weeks. At its core is a production graph RAG system connecting temporal and sentiment data at enterprise scale - a key technical differentiator. As a senior backend IC, you will work across the graph database layer, API infrastructure, and data pipelines with concurrency at scale. You will collaborate with ML/AI engineers to bring predictive and prescriptive models into production, own system reliability under high-throughput conditions, and shape the long-term technical trajectory of the platform. There is currently a staff backend engineer working across large parts of the stack - you will be additive senior capacity, not a replacement.

You have

5+ years of professional backend engineering experience building systems at scale

Strong Python proficiency; confidence that picking up Go would be no problem (Go experience is a plus)

Experience with distributed systems and microservices architecture

Comfort with both SQL and NoSQL databases and data processing at scale

Startup or small-team experience where you built new things with real ownership - not just maintained existing systems

Nice to have

Graph database experience (a major plus - core to the stack)

Go experience

Familiarity with RAG architectures and the broader GenAI landscape

Experience with real-time data processing, streaming technologies, and concurrency at scale

Understanding of ML/AI concepts, particularly forecasting and NLP

Kubernetes and container orchestration experience

What to do

Design, build, and scale backend services in Go and Python powering autonomous intelligence for enterprise clients

Architect data ingestion and processing pipelines handling millions of data points across internal and external sources

Build and maintain APIs serving the agentic AI platform, supporting real-time decision-making at enterprise scale

Work with the graph database layer and production graph RAG system

Collaborate with ML/AI engineers to integrate predictive and prescriptive models into production workflows

Own system reliability - design for fault tolerance, observability, and performance under high-throughput conditions

Contribute to architectural decisions that shape the long-term trajectory of the platform

Mentor engineers and help establish backend engineering best practices as the team scales

Interview process

Recruiter screen

Intro call

Technical screen with a senior engineer

On-site: coding, system design, product sense, AI sense, and a meeting with a co-founder

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