Principal - AI & ML Solutions

Job DescriptionKey Responsibilities 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. Education and Qualification 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, TensorFlow, LangChain, 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., LangChain Agents, AutoGPT, OpenAgents, 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.