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Remote role and AI demand increase applicants, but seniority and niche skills reduce density.
Highly domain-specific ML/AI and LLM expertise required, limiting cross-industry transferability.
Explicit 10+ years and many mandatory AI, cloud, and deployment skills create strict filters.
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Design, architect, and develop scalable AI capabilities integrated into a cloud-based SaaS platform used for business process automation.
Build robust, reliable AI systems leveraging technologies like LLM, RAG, LangChain, and various cloud AI services, ensuring 24/7/365 operational stability.
Collaborate with cross-functional teams to define and implement new AI features on a multi-tenant SaaS platform with a focus on maintainability and scalability.
10+ years of experience building large-scale cloud-based distributed applications.
Strong experience in multi-tenant SaaS application development and AI technologies including LLM models, RAG, LangChain, and LlamaIndex.
Proficient in Python and Java programming, with experience in NLP tools (spaCy, NLTK, Hugging Face Transformers) and model deployment frameworks (TensorFlow Serving, MLflow, Kubernetes).
Work Experience Required: 10+ years; Location/Work Mode: Remote; Language Proficiency: English at C1 level.
Senior-level engineer with demonstrated ability to design, build, and maintain complex AI-driven, cloud-native SaaS products at scale.
Experienced in microservices architecture, container orchestration (Docker, Kubernetes), and CI/CD for continuous deployment in a distributed team environment.
Strategic thinker comfortable with data-driven decisions, mentoring others, and collaborating across diverse, remote teams to innovate AI capabilities.