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Remote and mid-level AI engineer role increases applicant volume, though niche LLM/vector skills moderate competition.
Specialized LLM, RAG, and vector DB expertise increases domain specificity and reduces cross-industry transferability.
Explicit mandatory LLM/RAG, vector DB, Snowflake, and production ML requirements create stringent technical filters.
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Design and develop autonomous AI agents capable of reasoning, searching, and executing complex workflows beyond traditional chatbots.
Build and deploy AI-driven applications leveraging frameworks like LangChain and LlamaIndex, with focus on RAG pipelines and AI agent orchestration.
Engineer scalable data pipelines and semantic search layers for AI consumption using big data technologies, vector databases, and advanced SQL.
5+ years of professional experience in AI, data engineering, or related technology roles.
Strong expertise in LLM orchestration and AI agent development with 2+ years of hands-on experience.
Proficiency in big data processing using Python (Pandas/PySpark) or Scala, and data warehousing tools like Snowflake or Redshift.
B.Tech or M.Tech degree in Computer Science or related field.
Experienced in advanced AI techniques including transformer models (Gemini, GPT, Claude), prompt engineering, and fine-tuning.
Skilled in production-grade software practices including clean code, robust CI/CD, and ML observability.
Familiar with cloud deployment and scaling of AI solutions, preferably with AWS services such as Bedrock and Lambda.