> Markdown version of [/jobs/ext/1933900-software-engineer-customer-experience](https://www.wearedevelopers.com/jobs/ext/1933900-software-engineer-customer-experience). 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 Engineer - Customer Experience - **Company:** Okta, Inc. - **Location:** San Francisco, CA, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Amazon S3, Cloud Computing, Software Quality, Continuous Integration, Customer Data Management, Data Governance, Distributed Systems, Github, Python (Programming Language), Machine Learning, Scrum Methodology, Salesforce.Com, Software Deployment, Software Engineering, Systems Integration, Strategies of Testing, TypeScript, Workflow Management Systems, Apex Code, Enterprise Software Applications, Large Language Models, Prompt Engineering, Facebook Flow, Backend, Event Driven Architecture, Amazon Relational Database Service, AI Platforms, Optimization Algorithms, Deployment Automation, Atlassian Tools, Integration Frameworks, Api Design, Cloudwatch, Api Gateway, Software Version Control, Docker - **Published:** August 5, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p9zperu70w ## About the Role * 3+ years of professional software engineering experience, with at least 3+ years in customer-facing platforms, enterprise integrations, or CRM-driven systems. * Expertise in backend and application development using Python or Java, JavaScript 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 with CI/CD pipelines, source control workflows, and automated deployments using tools such as GitHub and Gearset. * 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 * 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. * Experience with containerization and orchestration technologies such as Docker and Kubernetes . * Exposure to advanced AWS services such as SageMaker, AppConfig, or event-driven architectures. * Track record of leading cross-functional technical initiatives or delivering large-scale platform improvements. What we value * Technical leadership and the ability to guide architecture, influence decisions, and elevate engineering practices across the team. * Strong engineering discipline, with a focus on clean design, maintainable code, observability, testing, and production excellence. * AI curiosity and pragmatism, balancing innovation with responsible, scalable implementation of emerging technologies. * Ownership mindset, taking responsibility from idea to implementation to operational success. * Mentorship and collaboration, with a genuine interest in helping others grow and working effectively across teams and functions. * Customer focus, with the ability to connect technical solutions to better customer and business outcomes. ## Description * Design and deliver 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. * Participate in 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., * Lead innovation at the intersection of enterprise customer platforms and cutting-edge AI technology. * Build intelligent, customer-facing solutions that have direct business impact and improve the overall customer experience. * Shape technical direction for AI-enabled capabilities across Salesforce, AWS, and modern integration platforms. * Work with a team that values engineering excellence, collaboration, and thoughtful adoption of emerging technologies. * Mentor engineers, influence architectural decisions, and play a key role in the evolution of our customer experience platform. 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