





Mid-level (4+) Bengaluru role at a known brand with a generic title increases applicant competition despite AI specialization.
Core LLM and ML skills transfer well, but enterprise device management and IoT experience increases domain specificity.
Requires explicit 4+ years plus specific LLM, RAG, production ML and integration expertise, making screening stringent.
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Design, develop, and deploy AI-powered capabilities to transform enterprise device management platform including intelligent search, conversational assistants, anomaly detection, predictive insights, automated remediation, and operational analytics.
Build scalable AI services, APIs, data pipelines, and integrations with existing platform workflows ensuring security, reliability, and cost-effectiveness.
Lead architecture and technical decisions related to AI adoption, governance, evaluation metrics, and cross-functional collaboration with product, engineering, security, and infrastructure teams.
Minimum 4+ years of software engineering experience building production-grade applications and services.
Hands-on experience with AI-powered or Generative AI applications including Large Language Models (e.g., OpenAI GPT, Claude, Gemini, Llama).
Proficiency in Python, Java, Kotlin or combination, plus experience with REST APIs, backend integrations, cloud AI services, and AI development frameworks.
Understanding of model confidence, evaluation metrics, AI governance, explainability, safe fallback mechanisms, anomaly detection, and auditability.
Experienced in building and integrating AI/ML solutions into large-scale enterprise platforms with focus on device management or related domains such as IoT or edge devices.
Skilled in implementing advanced AI features like RAG, semantic search, intelligent assistants, predictive analytics leveraging telemetry and operational data.
Able to lead technical architecture and collaborate cross-functionally translating business needs into AI solutions with strong emphasis on responsible AI practices and scalable production deployments.