Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 employer, metro location, and mid-level experience increase applicant competition despite LLM specialization.
Specialized LLM engineering skills are transferable across industries but require AI expertise and regulated environment familiarity.
Mandatory 3+ years plus specific LLM, Python, cloud, and security requirements enforce strict shortlisting.
Design, build, and productionize agentic AI workflows and LLM-powered applications (e.g., conversational interfaces, summarization, advisory assistants) with focus on security, audit, and operational reliability.
Implement tool integrations and RAG components with attention to authentication, authorization, logging, latency, and answer quality.
Lead design of distributed systems architecture, establish evaluation/monitoring pipelines, and mentor engineers to uphold engineering standards in AI delivery.
3+ years of applied software engineering experience with formal training or certification.
Strong Python proficiency and experience with APIs/microservices.
Hands-on experience with building LLM/RAG/agentic applications and familiarity with agent frameworks (e.g., LangChain, LlamaIndex).
Experience with cloud platforms (AWS or Azure), CI/CD, operational monitoring, and secure development practices; mandatory use of enterprise-authorized AI-assisted software development tools.
Experienced in AI-driven software engineering with demonstrated ability to deliver secure, compliant, and scalable AI applications in regulated or security-sensitive environments.
Proficient in building complex, multi-step AI workflows involving tool orchestration, error handling, and human-in-the-loop approvals.
Skilled in integrating AI features with data engineering and operational practices, validation of AI outputs, and guiding teams on responsible AI use and secure coding standards.