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Metro location and broad GenAI/NLP skillset increase applicant competition.
Core ML/NLP skills transfer easily across industries, so background sensitivity is low.
Explicit 6+ years plus specific GenAI, RAG, vector DB, and LLM experience required.
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Develop, deploy, and scale GenAI and agent-based AI/ML systems integrated into enterprise digital products, focusing on reasoning, planning, and semi-autonomous workflows.
Build components using LLMs, RAG pipelines, prompt engineering, and tool integration with APIs, microservices, and containerization.
Collaborate with cross-functional teams end-to-end for GenAI initiatives, ensuring scalable, reliable, and maintainable AI solutions following best practices.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or similar.
6+ years experience in AI/ML, software engineering, data or analytics with focus on digital solution development; 2-5 years core experience in NLP and GenAI solution development.
Hands-on experience with LLM ecosystems (OpenAI, Azure OpenAI, open-source models), RAG architectures, embeddings/vector databases, and prompt engineering.
Experience integrating applications using APIs, microservices, containerized environments; familiarity with software engineering best practices including version control, testing, CI/CD.
Experienced in building scalable, maintainable GenAI and agentic systems with knowledge of standard design patterns and production deployment.
Skilled in developing AI solutions for autonomous or semi-autonomous workflows using prompt engineering, tool chaining, and human-in-the-loop approaches.
Comfortable working in global, distributed teams collaborating with senior engineers, product owners, and business SMEs in a multicultural environment.