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AI-Powered Job Summary
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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
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