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Open nowPosted yesterday

Software Engineer - Platform

IBM3,077 open roles

Where
Multiple Cities
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Your applicationOpen nowSoftware Engineer - PlatformIBM · Multiple Cities

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

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The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. IBM postings stay open a median of 15 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: posted yesterday

IBM median: 15 days open

The posting

At IBM Software, we transform client challenges into solutions. Building the world's leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You'll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM's product and technology landscape. Here, you'l have the tools and opportunities to advance your career while creating software that changes the world.

  • IBM’s Platform team spans the globe, just like the products we support. We build and power the technology that helps organizations manage, scale, and secure the modern enterprise. As a Software Engineer on Platform@IBM, you’ll play an important role in developing the next generation of platform technology that supports IBM’s products and customers worldwide.
  • Own platform architecture end-to-end: design, build, and operate the high-throughput, low-latency infrastructure that underpins IBM's commercial cloud offerings.
  • Lead systems development — architect and implement the orchestration layers, runtimes, and multi-agent commercial patterns that enable workloads to operate reliably at scale.
  • Drive technical strategy in the face of ambiguity; scope large, loosely defined problems, decompose them into tractable work, and align cross-functional teams around a clear engineering direction.
  • Set the bar for system reliability and scale — define SLOs, lead capacity planning exercises, and engineer for failure across distributed services handling millions of requests per day.
  • Mentor and level up the engineering organization; author RFCs and design documents that raise the technical floor for the entire team.
  • Collaborate with product, research, and adjacent platform teams to translate emerging AI capabilities — including retrieval-augmented generation, agent tool use, and model inference pipelines — into production-grade platform primitives.
  • Champion engineering excellence: lead code reviews, drive adoption of observability and site reliability practices, and hold a high bar for testability, operability, and security.
  • Distributed systems & high-scale backend expertise: 4+ years designing distributed systems, including consensus, replication, partitioning, and latency/throughput/consistency trade-offs, plus production experience with systems handling tens of thousands to millions of RPS with 99.9%+ availability and strict latency requirements.
  • Backend development & cloud-native infrastructure: Proficiency in Go, Rust, Java, Python, and/or C++, with 5+ years building or operating production Kubernetes, OpenShift, or equivalent container orchestration and cloud-native infrastructure.
  • Agentic AI & emerging architectures: Familiarity with LLM-based reasoning loops, tool/function calling, agent-to-agent communication, and autonomous task execution frameworks, with the ability to apply these concepts in evolving technical environments.
  • Adaptability & commercialization: Demonstrated success in undefined, fast-moving environments where requirements evolve, along with experience supporting SaaS commercialization, including packaging, go-to-market flows, tenancy, and provisioning.
  • US Federal offerings: Experience supporting US Federal offerings and working closely with government partners in regulated environments.
  • Hands-on experience architecting multi-agent or agentic AI systems in production (orchestrators, planners, tool registries, memory/context stores) - 2 years
  • Background in developer platform or internal tooling at scale (CI/CD, observability, secrets management, API gateways, or platform control planes) - 5 years
  • Experience with event-driven architectures using Kafka, NATS, or similar high-throughput messaging systems – 5 years
  • Contributions to open-source platform or infrastructure projects.
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