> Markdown version of [/jobs/ext/2565185-software-engineering-lmts](https://www.wearedevelopers.com/jobs/ext/2565185-software-engineering-lmts). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineering LMTS - **Company:** Salesforce Inc. - **Location:** Bellevue, WA, United States - **Experience:** Expert - **Salary:** $172,500.0 - $260,100.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Multitier Architecture, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Client Server Models, CentOS, Software as a Service, Configuration Management, Code Review, Encodings, Cyber Security, Computer Programming, Computer Engineering, Information Engineering, Data Security, Cursor (Graphical User Interface Elements), Linux, Distributed Systems, Fault Tolerance, Apache Hadoop, Infrastructure as a Service (IaaS), Identity and Access Management, Python (Programming Language), Machine Learning, Model View Controller (MVC), NoSQL, OAuth, Object-Oriented Software Development, Platform as a Service (PAAS), Public Key Infrastructure, Red Hat Enterprise Linux, Swagger, Salesforce.Com, Security Assertion Markup Language (SAML), Single Sign-On, Software Engineering, SQL Databases, Technical Data Management Systems, Openapi, Data Processing, Multithreading, Google Cloud, Large Language Models, Prompt Engineering, Apache Spark, Software Security, Infrastructure Automation Frameworks, Maintaining Code, Apache Kafka, Puppet, Terraform, Data Pipelines, Docker, Vulnerability Analysis, Golang - **Published:** August 7, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9fff7b16fc0e3028 ## About the Role * Industry experience: 10+ years for LMTS, including 5+ years in SaaS, PaaS, or IaaS software development. * Education: M.Sc./B.E. in Computer Science Engineering (or equivalent experience). * Distributed systems and data engineering: Expertise designing, implementing, and operating high-scale distributed systems, including: + High-performance, high-availability (99.99%), and highly fault-tolerant systems + Large-scale infrastructure systems + Docker-based development, particularly with EKS + Configuration management systems, including Infrastructure-as-Code (IaC), Terraform, Puppet * Data technology: Apache Spark & Kafka, Hadoop, SQL/NoSQL. * Programming: Proficiency in object-oriented and multi-threaded programming in at least one of: Python, Golang, Java/Scala. * Software design: Demonstrated expertise applying system patterns (e.g., client-server, N-tier, primary/secondary, MVC) and API construction (e.g., Swagger, OpenAPI). * Operating systems: Experience developing and managing software on Linux (e.g., CentOS or RHEL). * Security: Strong foundational knowledge of security concepts - authentication/authorization frameworks (e.g., SSO, SAML, OAuth), secure transport (e.g., TLS), and identity management (e.g., certificates, PKI). * Applied AI/ML: Hands-on experience integrating LLMs or ML models into production systems, including at least two of: RAG pipelines, agent/tool-use frameworks (e.g., MCP, LangGraph), prompt engineering, evals/observability for LLM apps, fine-tuning, or embeddings/vector stores. * AI-assisted engineering: Demonstrated fluency with agentic coding tools (Claude Code, Cursor, Copilot, or equivalent) as a daily driver, with the ability to guide the team on effective and safe usage patterns. * Communication: Strong oral and written communication skills. * Able to manage multiple projects at once, meet deadlines, and adapt to shifting priorities. * Team orientation: Values team success alongside personal contributions.Vision execution: Able to translate strategic or operational goals into technical and tactical requirements and architecture design. Preferred/Nice-to-Have * Experience applying AI/ML to security use cases - e.g., anomaly detection, alert triage, vulnerability prioritization, or SOC automation. * Experience with MCP (Model Context Protocol), tool-use frameworks, or building agentic workflows on top of security data. * Familiarity with LLM cost/latency optimization, guardrails, prompt-injection defense, and evaluation frameworks. * Experience with vector databases and embedding-based retrieval over structured/unstructured security data. ## Description * Learn and adapt to Salesforce's security strategies, goals, objectives, and capabilities to help improve security posture. * Lead the design and architecture of a highly scalable and secure data platform that ingests and processes diverse security data sources across 10+ Salesforce platforms and 15+ external environments. * Build and optimize data pipelines to collect, store, and analyze security signals from tools and platforms (e.g., vulnerability scanners, asset management systems, identity and access control systems) running across multiple environments (AWS, GCP, Salesforce, CRM, vendor systems, etc.). * Design and integrate AI/ML and LLM-driven capabilities into the platform - including RAG over security data, agentic triage/remediation workflows, anomaly detection, and risk scoring - with strong attention to evals, guardrails, and cost/latency tradeoffs. * Work closely with cross-functional teams (e.g., Engineering, Security Operations, Risk Management, Product Security, and Data Science) to align the data platform with business and security goals. * Participate in an Agile development environment, including daily syncs. * Support the team's engineering excellence through code reviews and by mentoring senior team members. * Provide technical leadership to a team of engineers, driving best practices in software development, security, AI-assisted development, and cloud-native architecture. Mentor engineers at all levels, fostering a culture of continuous learning, innovation, and excellence. * Champion effective use of AI-assisted development tools (e.g., Claude Code, Cursor, Copilot) across the team - establishing patterns for agent-driven workflows, code review, and productivity while maintaining code quality and security. * Own and deliver initiatives that add new features to meet growing product demands. * Adapt quickly to changing requirements, priorities, and strategies.Advocate for security and secure practices throughout Salesforce, including secure AI/agent design (prompt injection defenses, least-privilege tool access, data handling for LLM contexts). ## Related Videos - [Keeping applications secure by evolving OAuth 2.0 and OpenID Connect](https://www.wearedevelopers.com/videos/100152-keeping-applications-secure-by-evolving-oauth-2-0-and-openid-connect) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Remote Driving on Plant Grounds with State-of-the-Art Cloud Technologies](https://www.wearedevelopers.com/videos/251-remote-driving-on-plant-grounds-with-state-of-the-art-cloud-technologies) - [Delay the AI Overlords: How OAuth and OpenFGA Can Keep Your AI Agents from Going Rogue](https://www.wearedevelopers.com/videos/1637-delay-the-ai-overlords-how-oauth-and-openfga-can-keep-your-ai-agents-from-going-rogue) - [Docker exec without Docker](https://www.wearedevelopers.com/videos/1094-docker-exec-without-docker) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)