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Metro location, mid-level generalist title, and high visibility increase applicant competition despite niche LLM requirements.
Specialized LLM/agent, RAG, and vector DB skills make the role less transferable outside AI-focused teams.
Multiple mandatory LLM, agentic-framework, and infrastructure skills create strict technical gating for candidates.
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Lead design and deployment of autonomous AI agents for resume optimization, job matching, AI interview, and career coaching features.
Develop multi-agent AI systems using frameworks like LangChain, AutoGen, or CrewAI, and integrate these across web and Chrome extension platforms.
Maintain RAG systems, vector databases, and implement prompt engineering for domain-specific LLMs ensuring scalability and performance.
Proficiency in LLM Engineering, Agentic AI Frameworks (e.g. LangChain, AutoGen, CrewAI), Python, OpenAI APIs or similar, Prompt Engineering, and Vector Databases.
Experience with Google Cloud Platform, Git, Firebase, Node.js, and Clickhouse.
Traditional Machine Learning experience is highly preferred.
Work Experience Required: Not explicitly mentioned in the JD; Location: Must work onsite up to 3 days/week in Delhi, India.
Experienced in building and scaling agentic AI systems using advanced LLM technologies in production environments.
Capable of collaborating asynchronously with a global remote engineering team and engaging cross-functionally with Product and Design.
Comfortable working 6 days a week with some US timezone overlap and potentially acting as a technical lead reporting to C-suite.