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Tier-1 employer, mid-level AI role, metro-office and broad GenAI skillset make competition high.
AI/ML and data engineering skills are broadly transferable across industries despite some enterprise compliance nuance.
Explicit minimum years plus required GenAI, data engineering, cloud, and production LLM/Ops skills indicate strict filtering.
Design, develop, and deploy enterprise AI applications and Generative AI solutions leveraging LLMs, Agentic AI, RAG, and knowledge retrieval architectures.
Develop scalable Python-based applications, APIs, microservices, and data engineering pipelines using cloud-native and distributed processing technologies.
Contribute to engineering best practices and AI/LLMOps frameworks to ensure production-ready, secure, and reliable AI solutions.
Minimum 2 years of software engineering experience or equivalent through education, training, or military service.
Proficiency in Python programming and development of scalable, high-performance applications.
Experience with cloud-native application development and microservices architecture (platforms such as GCP preferred).
Work Experience Required: 2+ years of software engineering experience (3-6 years preferred with AI/GenAI focus).
3-6 years of experience developing enterprise-scale applications and distributed systems with strong Python skills.
1-3 years of hands-on experience building Generative AI solutions using LLMs, LangChain, RAG, and related AI frameworks.
Expertise in data engineering and building scalable ETL/ELT pipelines using Spark, Databricks, and knowledge retrieval systems including vector databases and semantic search.