Senior, Software Engineer, Cryptographic Asset Monitoring

Salesforce•San Francisco, CA

2d•$148,500 - $246,000

About The Position

Salesforce is seeking a Senior Software Engineer to design, build, and operate backend systems that power critical infrastructure at scale. This role involves working on distributed, high-availability services, owning significant components end-to-end, and shaping how the team builds reliable software. The engineer will stay deep in the code while mentoring others, treating AI as a core part of their everyday development workflow, and contributing to technical decisions that shape system direction.

Requirements

6+ years of professional software development experience, with a track record of owning production systems end-to-end.
Strong proficiency in at least one backend programming language, such as Go, Java, Python, or Rust, and experience with distributed systems.
Experience designing and operating Representational State Transfer (RESTful) or gRPC services, including database design and query optimization.
Experience deploying and operating services in cloud environments, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
Strong understanding of Continuous Integration/Continuous Delivery (CI/CD) pipelines, testing practices, and modern software delivery workflows.
Ability to work independently on ambiguous problems and drive them to resolution.
Strong written and verbal communication skills.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Demonstrated, genuine AI-first approach to engineering, using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
Experience using AI tools, such as Claude Code, GitHub Copilot, Codex, or Cursor, in development workflows.
Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Nice To Haves

Experience with container orchestration, such as Kubernetes, and Infrastructure-as-Code paradigms.
Experience with observability tooling, including distributed tracing, metrics, and alerting, at scale.
Experience working in a regulated, multi-region, or high-compliance environment.
Familiarity with asynchronous processing, message queues, or event-driven architectures.
Deep domain knowledge of Public Key Infrastructure (PKI), X.509 certificate profiles, and mutual Transport Layer Security (mTLS) architectures.
Strong understanding of certificate lifecycle management and automated certificate provisioning.
Awareness of post-quantum cryptography (PQC) standards, such as Module-Lattice-Based Key-Encapsulation Mechanism (ML-KEM), and crypto-agility design principles.

Responsibilities

Design, build, and operate backend services and Application Programming Interfaces (APIs) that meet high standards for reliability, scalability, and performance.
Make sound architectural and technical tradeoffs on ambiguous, evolving requirements.
Write resilient, well-tested, and observable code that can be operated confidently in production.
Design and maintain data models, storage systems, and integrations that scale with growing usage.
Instrument services with logging, metrics, and tracing to support monitoring and fast incident response.
Debug and resolve complex production issues, identifying root causes and implementing durable fixes.
Participate in code reviews and design reviews, mentoring other engineers and raising the bar for engineering quality.
Partner with cross-functional stakeholders to translate requirements into scalable technical solutions.
Contribute to on-call rotations and incident response for the systems you own.
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow, pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Contribute to building and maintaining shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably, and critically evaluate code, whether human- or AI-generated, for correctness, quality, security, and performance.