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Remote hiring plus broad AI/MLOps and platform skills creates moderate competition.
Specialized agentic AI, MLOps, and distributed systems expertise limits cross-industry transferability.
Explicit 8+ years, mandated AI/ML platform experience, and specific tooling requirements make screening highly strict.
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Design, build, and maintain a centralized AI platform with unified APIs enabling secure deployment and management of AI agents across teams.
Integrate AI agents into customer-facing and internal applications by collaborating with Product Engineering and cross-functional teams.
Lead technical vision setting, mentor engineers, and ensure security, compliance, and scalable performance of AI platform workloads.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
8+ years of software engineering experience, including 2+ years on AI/ML platforms or infrastructure.
Proficiency in Python and experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
Experience with containerization/orchestration (Docker, Kubernetes), MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, Databricks), and cloud platforms (AWS, GCP, Azure).
Experienced in building large-scale distributed systems and microservices focused on AI/ML infrastructure.
Capable of leading technical strategy and mentoring to shape a scalable, secure AI platform.
Skilled in cross-team collaboration to integrate AI solutions into diverse product environments.