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Remote role and known multinational brand increase applicants, but senior AI+fullstack specialization reduces density.
Requires deep AI, cloud, and fullstack engineering expertise, making skills less transferable across unrelated industries.
Extensive mandatory stack (Python, AWS, Kubernetes, LLMs, PostgreSQL, GPU, Lean Six Sigma) implies strict technical filters.
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Design, build, and deploy end-to-end full-stack AI applications integrating backend AI models and user-friendly frontends.
Develop and optimize backend services, APIs, complex SQL database architectures, and real-time data pipelines using Python and PostgreSQL.
Manage cloud infrastructure (AWS), containerization (Docker), orchestration (Kubernetes), and Linux operations to ensure scalable, high-performance AI deployments.
Proven hands-on experience with advanced Python development and AI application deployment.
Strong expertise with AWS cloud infrastructure, Docker, Kubernetes, and Linux system administration.
Experience in designing and optimizing relational databases, preferably PostgreSQL, with advanced SQL skills.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in multi-agent AI systems and Retrieval-Augmented Generation (RAG) architectures integration into production environments.
Demonstrated ability to lead technical teams, mentor junior developers, and communicate complex AI solutions to diverse stakeholders.
Familiarity with quality frameworks such as Lean Six Sigma to maintain operational excellence and high-reliability software.