Senior Software Engineer
Okta
| Company | Okta |
| Category | Engineering |
| Location | Warsaw |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 9 Mar 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
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. We are seeking an independent Senior Software Engineer who effectively balances technical excellence with a disciplined approach to the software development lifecycle. egrity of our environments.
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
5+ 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 des
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