Key Responsibilities
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Design, develop, and deploy Generative AI solutions using AWS Bedrock, SageMaker, and related AI/ML services.
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Collaborate with stakeholders to identify use cases, define solution architecture, and deliver POCs and production deployments.
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Provide guidance on best practices, cost optimization, and security for Gen AI projects.
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Stay updated on the latest in LLMs, foundation models, and responsible AI practices.
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Conduct workshops, demos, and presentations for both technical and non-technical audiences.
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Partner with data engineers, ML engineers, and product teams for end-to-end AI solution delivery.
Required Skills & Qualifications
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Strong expertise in AWS Cloud ecosystem (Bedrock, SageMaker, Lambda, API Gateway, security services).
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Proven experience building LLM-based solutions (e.g., chatbots, summarization, knowledge retrieval, agents).
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Solid understanding of vector databases, prompt engineering, and RAG (Retrieval-Augmented Generation).
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Proficiency in Python and ML/AI libraries (PyTorch, TensorFlow, LangChain).
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Excellent communication and client-facing skills with ability to simplify technical concepts.
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Self-driven, proactive, and able to thrive in fast-paced, ambiguous environments.
Nice-to-Have
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AWS Certifications (e.g., Machine Learning Specialty, Solutions Architect).
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Experience with other Gen AI platforms (Azure OpenAI, Google Vertex AI).
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Familiarity with MLOps and deployment pipelines for Gen AI applications.
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Prior consulting or client engagement experience.