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Strong brand, popular AI title, mid-level experience, and metro locations drive high competition.
Specialized generative AI and regulated-bank delivery experience limits transferability moderately.
Many mandatory LLM/MLOps skills plus explicit 5+ years and regulated governance requirements make filters strict.
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Design, develop, and deploy scalable machine learning and generative AI systems, including fine-tuning LLMs and building Retrieval-Augmented Generation (RAG) pipelines.
Build and manage vector databases and agentic AI workflows using frameworks like LangChain and orchestration tools such as Temporal for reliable multi-step AI processes.
Lead AI delivery planning, risk and governance management, and collaborate with cross-functional teams to translate business requirements into AI/ML technical solutions.
Bachelor's or Master's degree in Computer Science, Engineering, or related discipline; AI/ML specialization preferred.
5+ years of software delivery experience with proven track record in complex AI/ML or data-driven solutions.
Strong proficiency in Python, AI/ML frameworks, LLMs, RAG architectures, vector databases, and agentic AI systems.
Experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes), workflow orchestration (Temporal, Airflow), and MLOps/LLMOps tools.
Experienced in end-to-end AI/ML system delivery in regulated enterprise environments focusing on risk, governance, and compliance.
Proven capability in cross-functional stakeholder management and leading AI engineering teams toward business-aligned AI solutions.
Deep technical expertise in AI orchestration frameworks and durable multi-agent workflows, with the ability to operationalize cutting-edge generative AI models at scale.