You'll work at the fascinating intersection of GenAI and cloud platform development, implementing automation solutions that directly enhance the productivity of our engineers. Unlike typical roles, you'll have the opportunity to influence both AI implementation and core architecture while collaborating with cloud technology experts.
The position offers rare exposure to latest cloud computing technology combined with the latest advances in artificial intelligence. You'll be part of a team that values technical excellence, working in an environment where your ideas can quickly transform from concept to reality.
In this role you will create solutions that directly shape the way we work. You'll develop smart automation systems, implement AI-driven tools and workflows and be part of AI transformation.
Key job responsibilities:
* Architect and deploy AI-powered solutions and AWS cloud services that transform development workflows.
* Lead technical innovation by driving architectural decisions and GenAI technology adoption.
* Champion AI transformation across engineering teams through education and hands-on implementation.
* Partner with elite cloud teams to identify opportunities and deliver advanced solutions.
* Ensure system excellence through participation in on-call rotations and reliability initiatives.
Basic Qualifications:
– 5+ years of hands-on software development experience.
– High-level Python programming skills.
– Solid foundation in AI/GenAI concepts and applications.
– Mastery of software design patterns and engineering best practices.
– Bachelor's degree in Computer Science or equivalent technical field.
– Customer-focused mindset with strong communication skills.
– Self-driven learner with exceptional ownership mentality.
– Collaborative team player who thrives in fast-paced environments.
Preferred Qualifications:
– Production experience with AI/GenAI infrastructure (LLM pipelines, RAG systems, prompt engineering, AI agents, MCP).
– Hands-on expertise with GenAI development frameworks (Kiro, Cursor, Cline, etc.).
– Deep knowledge of AWS serverless and cloud infrastructure (Lambda, CDK, S3, SQS, etc.).
– AWS certifications (Practitioner, Developer, Solutions Architect) – valued but not required
