What You'll Actually Be Doing
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by 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 the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
Critically evaluate code (human or AI-generated) for correctness, quality, security, and performance.
Build new and exciting components in an ever-growing and evolving market technology to provide scale and efficiency.
Develop high-quality, production-ready code that can be used by millions of users of our cloud platform.
Make design decisions on the basis of performance, scalability, and future expansion.
Work in a Hybrid Engineering model and contribute to all phases of SDLC including design, implementation, code reviews, automation, and testing of the features.
Build efficient components/algorithms on a microservice multi-tenant SaaS cloud environment.
Code review, mentoring junior engineers, and providing technical guidance to the team (depending on the seniority level).
Requirements: You're Our Person If...
8+ years of development experience as a software engineer.
Deep knowledge of object-oriented programming and other scripting languages: Java, Python, Scala C#, Go, Node.JS and C++.
Strong SQL skills and experience with relational and non-relational databases e.g. (Postgres/Trino/redshift/Mongo).
Experience with developing SAAS products over public cloud infrastructure - AWS/Azure/GCP.
Proven experience designing and developing distributed systems at scale.
Proficiency in queues, locks, scheduling, event-driven architecture, and workload distribution, along with a deep understanding of relational database and non-relational databases.
A demonstrated, genuine AI-first approach to engineering - using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows.
Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate the system context that makes AI outputs reliable, secure, and production-ready.
A deeper understanding of software development best practices and demonstrate leadership skills.
Degree or equivalent relevant experience required. Experience will be evaluated based on the core competencies for the role (e.g. extracurricular leadership roles, military experience, volunteer roles, work experience, etc.).
Even Better If...
Technical expertise in Generative AI, particularly with RAG systems and Agentic workflows that use large language models.
Experience with Big-Data/ML and S3.
Hands-on experience with Streaming technologies like Kafka.
Experience with Elastic Search.
Experience with Terraform, Kubernetes, Docker.
Experience working in a high-paced and rapidly growing multinational organization.
This position is open to all candidates.