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High—Tier-1 brand, metro location, mid-level role, and broad GenAI requirements amplify competition.
High—specialized GenAI, LLMs, vector DBs, and integration expertise required restricts cross-industry transferability.
High—explicit 5+ years, mandatory GenAI frameworks, Python, cloud, and enterprise integration skills.
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Design, develop, and deploy AI-powered applications and production-ready solutions leveraging LLMs, RAG architectures, AI agents, and integration frameworks.
Build backend services, APIs, user interfaces and integrate AI foundation models and services across platforms such as Azure OpenAI, Anthropic Claude, and Google Vertex AI.
Optimize AI applications for quality, scalability, performance, and cost-efficiency, including implementing testing, monitoring, and collaborating with cross-functional teams to deliver scalable solutions.
Minimum 5+ years of relevant experience in AI software engineering and development.
Master of Business Administration (MBA) degree mandatory.
Strong proficiency in Python and experience with API frameworks like FastAPI or Flask.
Hands-on experience with Generative AI technologies including LLMs, prompt engineering, RAG architectures, and AI platforms (Azure OpenAI, OpenAI, Anthropic Claude, Google Vertex AI, AWS Bedrock, etc.).
Experienced in developing enterprise-grade AI applications with a focus on integrating generative AI models and multi-agent systems.
Capable of optimizing AI solution delivery balancing quality, performance, and cost in cloud environments (Azure, AWS, or GCP) including containerization and CI/CD practices.
Familiar with AI governance, evaluation/observability tools, and implementing responsible AI practices within a consulting and advisory context.