Staff Software Engineer

Role details

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Okta is The World’s Identity Company. We free everyone to safely use any technology anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at the heart of business security and growth. At Okta, we celebratea a variety of perspectives and experiences. We are not looking for someone who checks every single box—we’re looking for lifelong learners and people who can make us better with their unique experiences. We are seeking an independent Staff Software Engineer who effectively balances technical excellence with a disciplined approach to the software development lifecycle. What you'll be doing Design, build, and evolve intelligent customer experience solutions that integrate Salesforce CRM with AWS services and modern generative AI capabilities. Architect and develop AI-powered experiences using Amazon Bedrock, LangChain, and modern LLM integration patterns to create context-aware, scalable, and customer-facing solutions. Build robust backend services and integrations to support customer workflows, including LLM orchestration, prompt workflows, RAG pipelines, and other generative AI features. Lead the design and delivery of complex customer experience initiatives from technical discovery through production deployment, ensuring scalability, reliability, and maintainability. Develop and refine prompt engineering strategies, grounding approaches, and AI interaction patterns that improve the quality, relevance, and safety of customer-facing AI experiences. Design and implement resilient APIs, event-driven integrations, and backend services that connect Salesforce, AWS platforms, internal systems, and external applications. Drive engineering excellence through strong CI/CD practices, using GitHub, Gearset, and deployment automation to support reliable and efficient releases. Champion observability, operational excellence, and production support practices to ensure enterprise-grade reliability, performance, and supportability of customer-facing systems and AI services. Mentor junior and mid-level engineers through technical guidance, code reviews, design reviews, and hands-on collaboration, raising the bar on engineering quality across the team. Lead technical decision-making across architecture, integration design, AI/ML tooling, scalability, security, and long-term platform evolution. Partner closely with product managers, designers, architects, security, data, and infrastructure teams to ensure solutions are aligned, secure, reliable, and enterprise-ready. Collaborate effectively in a Scrum-based Agile environment, using Jira and Confluence to drive execution, document decisions, and maintain delivery transparency. Evaluate emerging AI/ML technologies, frameworks, and engineering patterns, and apply them pragmatically to improve customer experience and operational efficiency. What you'll bring to the role 8+ years of professional software engineering experience, with at least 3+ years in customer-facing platforms, enterprise integrations, or CRM-driven systems. Strong expertise in backend and application development using Python or Java, JavaScrip or TypeScript, with the ability to build production-grade, scalable software systems. Strong experience designing and building cloud-native solutions on AWS , including services such as Lambda, S3, RDS, API Gateway, and CloudWatch, with a focus on scalability, resilience, and security. Proven experience integrating LLMs and generative AI capabilities into production-ready applications, ideally using Amazon Bedrock, LangChain, or similar frameworks. Experience building AI-powered backend services such as prompt orchestration layers, RAG workflows, retrieval pipelines, or other intelligent application patterns. Strong software engineering fundamentals, including distributed systems design, API development, testing strategies, code quality, and maintainable architecture. Experience building and supporting CI/CD pipelines, source control workflows, and automated deployments using tools such as GitHub and Gearset. Ability to lead architecture discussions, influence technical strategy, and make sound engineering decisions across multiple systems and stakeholders. Demonstrated experience mentoring engineers and helping teams improve engineering practices, technical quality, and delivery maturity. Strong working knowledge of Agile/Scrum delivery models, and experience partnering across product, engineering, and business teams in sprint-based execution. Excellent communication skills with the ability to explain complex technical ideas clearly to both technical and non-technical audiences. Nice to have Deep hands-on experience with Salesforce architecture and development, including Apex, Lightning, Flow, APIs, and data models, with a strong understanding of enterprise CRM workflows. Experience with advanced prompt engineering, evaluation strategies, and optimization techniques for customer-facing AI applications. Familiarity with vector databases, embeddings, and Retrieval-Augmented Generation (RAG) architectures. Experience with LangGraph, LangSmith, agentic workflows, or related frameworks for orchestrating more advanced AI application behavior. Background in enterprise security, compliance, and data governance , especially as it relates to AI adoption and customer data protection. Experie