Staff Software Engineer, Stream Processing & Analytics

IBM

Confirmed live yesterday High trust

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Work type: On-site
Location: —
Posted: 6 days ago
Freshness: Confirmed live yesterday

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How this pay compares to similar roles

Similar $211k

$161k most similar roles pay here $273k

This listing doesn't post a salary. Most similar roles pay $176,600–$246,000.

Based on 240 similar postings.

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IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

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TL;DR · Staff Software Engineer, Stream Processing & Analytics

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Confluent - Staff Software Engineer - Stream Processing & Analytics joins the team building Confluent Cloud's AI capabilities, which allow customers to integrate AI and agent capabilities directly into real-time data streams. This role involves designing and building backend services for model inference on streaming data while owning features end-to-end, from drafting designs to ensuring production reliability. The engineer will navigate complex systems including user-facing APIs, model lifecycle management, and execution layers. Key technical requirements include proficiency in Go, Java, or Python, along with deep expertise in Kubernetes and distributed systems patterns like control loops and high-scale control planes. The role focuses on the infrastructure for serving AI reliably at scale rather than machine learning research. Candidates must demonstrate experience in cloud-native backend infrastructure to solve problems involving inference routing and agent execution within a streaming data environment.

What does a Software Engineer earn?

Median $195000 from 1914 postings across 140 companies.

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Skills

Go Java Python Kubernetes Distributed Systems Cloud-native Containerization Networking API Streaming Data Model Serving Inference Backend Services

What you'll do

Design and build backend services in Go, Java, or Python to run AI and model inference on real-time data.
Own features end-to-end by drafting designs, aligning stakeholders, and driving technical decisions to a conclusion.
Make critical technical calls for systems spanning multiple teams, including model lifecycle, inference routing, and agent execution.
Ensure high quality of production infrastructure through rigorous code, testing, documentation, and rollout safety.
Mentor other engineers through active code reviews and providing feedback on complex design problems.
Participate in on-call rotations to maintain the reliability and health of owned services.

What we're looking for

Master's Degree (preferred).
10+ years of experience designing, building, and operating distributed systems or cloud-native backend infrastructure in production.
Strong working knowledge of Kubernetes and distributed-systems patterns including control loops, API servers, and high-scale control planes.
Proficiency in at least one of Go, Java, or Python with a willingness to work across all three.
Proven track record of leading cross-team technical work by turning ambiguous requirements into designs.
Excellent written and verbal communication skills for creating design documentation that aligns stakeholders.
Exposure to model serving, LLM/agent infrastructure, or streaming data systems (preferred).

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