As a Full Stack Software Engineer, your job responsibilities will include:
Build new and exciting components in an ever-growing and evolving market technology to provide scale and efficiency.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.
Code review, mentoring junior engineers, and providing technical guidance to the team (depending on the seniority level)
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.
Requirements: 5+ 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++.
Proven understanding of web technologies, such as JavaScript, CSS, HTML5, XML, JavaScript, JSON, and/or Ajax.
Experience with developing SAAS products over public cloud infrastructure - AWS/Azure/GCP.
Proven experience designing and developing distributed systems at scale.
A deeper understanding of software development best practices and demonstrate leadership skills.
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.
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.)
Desired Skills:
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.