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Tier-1 brand, metro location, and broad senior ML/AI skillset increases qualified candidate density.
Highly specialized ML/AI, data engineering, and financial services experience limits cross-industry transferability.
Explicit 10+ years plus mandatory ML, data engineering, cloud, and enterprise finance experience make filters strict.
Lead design and development of AI/ML microservices and distributed architectures with RESTful APIs.
Drive deployment and optimization of GenAI solutions including prompt engineering and workflow design for large-scale financial services.
Manage cloud-native architecture implementation and enterprise-scale agile delivery under SAFe framework.
10+ years of experience in microservices, RESTful APIs, and distributed architectures.
Proficiency in AI/ML technologies including Python, FastAPI, Java, PyTorch, TensorFlow, and foundational AI models (Gemini, OpenAI, Claude, Llama).
Experience with cloud platforms (AWS, Azure, GCP) and data engineering (pipelines, warehouses, lakes, batch/stream processing).
Familiarity with SAFe Agile, DevOps, CI/CD, container orchestration, and financial services enterprise environments.
Senior engineer capable of architecting and deploying complex AI/ML solutions in microservice-based, cloud-native environments.
Experienced in integrating AI foundational models with orchestration and retrieval augmented generation techniques for scalable financial applications.
Able to lead agile delivery with effective stakeholder management and executive communications.