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Tier-1 brand and mid-level ML role increase competition, niche agentic specialization partially reduces applicant pool.
Specialized agentic AI skills are somewhat transferable across industries but remain domain-specific and sought-after.
Mandatory ML/agentic skills, solution architecture, and specific tool expertise will create strict candidate filtering.
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Design, develop, and optimize autonomous AI solutions including agent orchestration, memory management, and integration with external tools.
Transform existing automation processes into intelligent, autonomous and semi-autonomous workflows to improve efficiency and scalability.
Document and implement technical architectures and best practices for scalable AI-driven automation solutions with human-in-the-loop components.
Bachelor’s degree with experience in AI/ML engineering and solution development.
Strong experience in AI/ML engineering, solution architecture, and end-to-end AI solution delivery.
Deep knowledge of RAG, prompt engineering, vector databases, embeddings, model evaluation, LLMs, generative AI, and agentic AI frameworks.
Experience with software engineering best practices including APIs, automation platforms, version control, testing, CI/CD, deployment, and responsible AI principles (governance, security, privacy).
Technical leader skilled in developing and orchestrating complex autonomous AI solutions using LLMs and generative AI technologies.
Experienced in building scalable AI automation workflows integrating human-in-the-loop and guardrail mechanisms for operational robustness.
Familiar with cloud deployment, MLOps, and modern AI infrastructure automation practices (Terraform, IaC) to support enterprise-scale AI applications.