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Metro location and mid-level hiring increase competition, but niche LLM/agent skills narrow the candidate pool.
Generative AI and LLM skills are easily transferable across industries despite adtech-specific knowledge being helpful.
Multiple mandatory ML/LLM, RAG, vector DB, and framework proficiencies plus degree requirement increase filtering.
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Lead end-to-end design, development, and deployment of AI-driven features in generative AI and AI agent platforms.
Implement and optimize large language models (LLMs) and retrieval-augmented generation (RAG) systems integrating vector databases for efficient and scalable search.
Collaborate with cross-functional teams to integrate AI capabilities into products while ensuring system reliability, scalability, and alignment with technical roadmaps.
2 to 10 years of experience with strong understanding of LLMs, transformer architecture, and AI agent development.
Bachelor’s degree in engineering or equivalent from a recognized institute/university.
Proficiency in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
Experience with vector databases (e.g., FAISS, Pinecone, Weaviate) and knowledge of indexing algorithms.
Experienced in designing AI agents including multi-agent orchestration, memory architecture, and use of agent frameworks like LangGraph, CrewAI, or AutoGen.
Skilled in prompt engineering and performance evaluation of AI models using tools like Evals.
Able to work in fast-paced Agile environments with a strategic mindset for scalable, secure AI architectures aligned to business needs.