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Well-known employer, mid-level ML role in Bangalore with popular title and production LLM requirements increases candidate competition.
Role demands specialized ML/GenAI production experience and agent orchestration, reducing cross-industry transferability.
Explicit 4+ years plus mandatory production LLM, Kubernetes, and agent-orchestration skills create strict shortlisting filters.
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Design and architect end-to-end AI agentic workflows to solve multi-step business problems, including agent orchestration and integration of custom and standard agents.
Develop, deploy, and continuously optimize AI/ML models covering traditional machine learning and large language model applications with strong focus on transparency and risk mitigation.
Build production-grade AI solutions using containerization (Docker, Kubernetes), API development, and adherence to coding standards and CI/CD processes.
4+ years of software engineering experience delivering AI/ML models to production.
Hands-on experience with agent orchestration frameworks such as LangGraph or AutoGen.
Expertise in containerization and orchestration technologies: Docker and Kubernetes.
Strong proficiency in both traditional ML tools (e.g., Scikit-learn, Pandas) and modern GenAI/LLM development.
Experienced with complex multi-agent AI systems and hybrid approaches combining out-of-the-box and custom agents.
Possesses a deep observability mindset, implementing logging and tracing in non-deterministic AI workflows.
Effective communicator able to translate complex AI concepts to business stakeholders and quickly prototype AI innovations.