Senior Manager - AI & ML

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• Independently design and implement end‑to‑end AI, Generative AI, and agentic AI solutions, taking full technical ownership of architecture, development, deployment, and optimization.
• Architect and build frameworks for autonomous AI agents capable of planning, reasoning, and executing multi‑step tasks using APIs, tools, enterprise systems, and external services.
• Develop robust integration patterns for LLMs, ML models, and agentic systems with enterprise applications, including databases, APIs, and legacy platforms, enabling intelligent tool‑using agents.
• Hands‑on model selection, fine‑tuning, evaluation, and optimization for LLMs, transformer‑based architectures, diffusion models, and other advanced AI models.
• Design advanced system components such as agent memory, reflection loops, vector stores, and long‑horizon planning mechanisms to support scalable agentic intelligence.
• Work closely with cross‑functional stakeholders to identify automation and augmentation opportunities, translating business needs into AI architecture and actionable solution designs.
• Implement strong governance, compliance, and Responsible AI controls, ensuring transparency, security, and safe deployment of all autonomous and generative systems.
• Define and operationalize monitoring, observability, and performance evaluation frameworks for continuous improvement of AI models and agentic systems.
• Drive cost optimization strategies across AI infrastructure, training pipelines, inference workloads, and cloud resource utilization.
• Ensure measurable value realization by validating that implemented AI solutions deliver tangible business impact and align with organizational objectives.
• Collaborate with the AI/ML engineering community and provide technical direction when needed, while maintaining personal hands‑on ownership of core development activities.

• Master’s degree (preferred) or Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
• Advanced certifications or specialization in AI/ML architecture, cloud platforms, or generative AI technologies are a plus.
• Certification in Databricks, Azure AI Engineer or Azure Data Scientist Associate.
• 8‑10 years of experience in AI/ML solution design and architecture, including at least 4+ years in Generative AI and agentic AI systems.
• Proven track record in architecting large‑scale AI platforms, integrating LLMs, and designing multi‑agent systems.
• Strong proficiency in Python and deep understanding of ML frameworks (e.g., PyTorch, Tensor Flow, Lang Chain, Hugging Face Transformers).
• Expertise in LLMs (e.g., GPT, Claude, LLaMA), vector databases, and prompt engineering strategies.
• Hands‑on experience with agentic frameworks (e.g., Lang Chain Agents, AutoGPT, Open Agents, CrewAI) and orchestration of autonomous agents.
• Deep knowledge of planning, reasoning, and decision‑making architectures for autonomous systems.
• Experience in cloud‑native AI architecture on Azure, including Azure ML/AI platform, Copilot Studio, and Azure Foundry.
• Strong background in containerization and orchestration (Docker, Kubernetes) for scalable AI deployments.
• Familiarity with reinforcement learning, symbolic reasoning, and neuro‑symbolic AI approaches.
• Experience with real‑time data processing, event‑driven architectures, and MLOps best practices for production‑grade AI systems.

• Mid‑Senior level

• Full‑time

• Engineering and Information Technology