Software Engineer (MTS), Frontier Strike (EntSecTech)

Salesforce; Washington; On-site; USD 120,000 - 180,000; Full time

Job summary

Salesforce is seeking a software engineer to design and extend Go microservices that orchestrate multi-container test suites on AWS. You will implement policy-based gateways, RBAC, and secrets isolation, while ensuring efficient AI-enhanced development workflows.

Required 2–4 years of experience with Go and distributed systems, plus Kubernetes, Docker, Helm, and Terraform in an AWS environment. Familiarity with REST/gRPC APIs is preferred.

Qualifications

• 2-4 years of professional software development experience.
• Proficiency in Go; Python or Java also acceptable.
• Experience with distributed systems, microservices, and REST or gRPC APIs.

Responsibilities

• Design and extend Go microservices that orchestrate multi-container test suites.
• Build policy-based sidecar gateways with least-privilege controls.
• Implement pipeline stages to deduplicate, suppress noise, and escalate findings.
• Design per-test-suite secrets isolation with automated credential rotation.
• Deploy and operate containerized workloads on Kubernetes via Helm/Terraform on AWS.
• Integrate with internal LLM gateway services to track token usage and costs.
• Implement RBAC, network sandboxing, and geofencing for safe test-to-prod migration.
• Monitor and troubleshoot distributed components to ensure data integrity.
• Deliver high-quality, production-grade software with AI as a core workflow.
• Design and orchestrate systems where AI agents integrate into human workflows.
• Contribute to building shared system context and standards for reliable AI operation.

Skills

Go

Python

Java

Distributed systems

Microservices

REST APIs

gRPC

Kubernetes

Docker

Terraform

AWS

AI-first approach

Education

Bachelor's degree in Computer Science

Tools

Helm

Terraform

CI/CD pipelines

Job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Software Engineering

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

The Experience

Frontier Strike, part of Enterprise Security Technology (EntSecTech), builds and operates the Harness Orchestrator, an autonomous AI red-teaming platform that continuously tests our own identity and AI-integrated systems the way a real attacker would. This role builds the orchestration engine, policy gateways, and secrets-isolation systems that let the team safely point automated adversarial testing at production. AI serves as a core part of the development workflow here, pairing hands-on distributed-systems engineering with modern AI-assisted tooling to ship secure, production-grade code faster.

What You'll Actually Be Doing

• Design and extend Go microservices that orchestrate multi-container test suites (primary and utility containers, shared ephemer...


• Build policy-based sidecar gateways that mediate every test suite's access to its target system, whether mocked, staging, or production, enforcing least-privilege and blast-radius limits as tests move up the risk tiers.


• Implement pipeline stages that dedupe, suppress noise, and auto-escalate critical findings (injection, server-side request forgery (SSRF), privilege escalation, data exfiltration) so only real signal reaches the persistent findings store.


• Design per-test-suite secrets isolation (dedicated vault, pod, and service account per suite) with automated credential rotation, so a compromised or misbehaving test suite can't reach another suite's credentials.


• Deploy and operate containerized workloads on Kubernetes via Helm and Terraform on Amazon Web Services (AWS), at a scale where individual test runs can cost significantly more or less depending on suite complexity.


• Integrate with internal large language model (LLM) gateway services to track token usage and cost per scan, and build throttling and authorization controls for expensive test executions.


• Implement role-based access control (RBAC), network sandboxing, and geofencing so automated red-teaming can be safely extended from test environments to production.


• Monitor and troubleshoot the platform's distributed components, ensuring findings-pipeline data integrity and proactively catching misconfigurations before they become production incidents.


• 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. Critically evaluate code, whether human- or AI-generated, for correctness, quality, security, and performance.

You're Our Person If...

• 2 - 4 years of professional software development experience.


• Demonstrates proficiency in Go; experience with Python or Java is also acceptable.


• Has experience with distributed systems, microservices, and Representational State Transfer (REST) or gRPC application programming interfaces (APIs).


• Is familiar with Kubernetes, Docker, Helm, and Terraform in a cloud environment, AWS preferred.


• Understands software security fundamentals: the OWASP Top 10, least privilege, and secrets management.


• Shows strong problem-solving and debugging skills in distributed, containerized systems.


• Works comfortably in a large-scale enterprise environment with production-safety constraints.


• Takes a demonstrated, genuine AI-first approach to engineering, using AI to move faster, build fluency across the stack, and contribute well beyond a core specialty.


• Has experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor) in development workflows.


• Applies advanced prompt engineering skills, writing precise, structured prompts and cultivating the system context that makes AI outputs reliable, secure, and production-ready.

A Bachelor's