About the Role

We are seeking a high-caliber Senior AI/ML Engineer (GEO/AEO Specialist) to lead the technical design, deployment, and optimization of production-grade AI systems tailored for Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), and Search Generative Experience (SGE).

In this role, you will bridge the gap between advanced Machine Learning, Information Retrieval, and modern AI Search ecosystems. You will build and fine-tune Large Language Model (LLM) architectures, Retrieval-Augmented Generation (RAG) pipelines, and ranking models designed to maximize content discoverability, semantic entity alignment, and citation ranking across platforms like ChatGPT, Google Gemini, and conversational AI search engines.

Key Responsibilities

• GEO/AEO & SGE Strategy Execution: Lead engineering initiatives to optimize content, data structures, and entity graphs for maximum discoverability and citation authority across generative AI search interfaces.
• AI/ML & GenAI Development: Design, build, and deploy production-scale Generative AI applications leveraging LLMs, NLP, semantic search, vector databases, and embeddings.
• Retrieval & RAG Architecture: Construct and evaluate robust Retrieval-Augmented Generation (RAG) frameworks, fine-tuning retrieval pipelines, context injection, and prompt orchestration.
• Ranking & Signal Modeling: Analyze AI response generation patterns, conversational search intent, vector similarity thresholds, and ranking signals to build predictive rank models for AI answer engines.
• Evaluation & Benchmarking Frameworks: Build rigorous experimentation and measurement frameworks to track GEO/AEO effectiveness, citation rates, latency, relevance, and model accuracy.
• Content & Schema Structuring for AI: Architect structured data schemas, knowledge representation graphs, and semantic layers for efficient AI/LLM parsing and consumption.
• Cross-Functional Collaboration: Partner with Product, SEO, Content, and Core Engineering teams to translate organic discoverability goals into high-impact AI models.

Required Skills & Qualifications

Mandatory Requirements:

• Experience: 5 to 7 years of overall AI/ML engineering experience, including 5+ years specializing in rank modeling, GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or SGE.
• GenAI & RAG Expertise: Hands-on development experience with prompt engineering, dense embeddings, vector search (Chroma, Pinecone, Weaviate, etc.), and end-to-end RAG workflows.
• AI Search Dynamics: Deep technical understanding of how AI engines (ChatGPT, Google Gemini, Perplexity) parse, rank, synthesize, and cite source data during generative retrieval.
• Semantic & Entity Optimization: Solid grasp of entity-based modeling, structured schemas, knowledge graphs, and semantic search algorithms.
• Core Technical Stack: Advanced proficiency in Python, modern NLP frameworks, and scalable machine learning libraries.
• Company Background: Must come exclusively from Top-Tier, High-Scale Product Companies (Tier-2 service or non-scale companies will not be considered).
• Target Education: B.Tech or Dual Degree (B.Tech + M.Tech / Integrated MS/M.Sc) from Tier-1 Engineering Institutes (IITs, NITs, BITS, VIT, DTU, NSUT).
• Resume Requirement: CV must clearly highlight quantifiable outputs, metrics, and architecture implementations of previous GEO / AI Engineering initiatives.

Work Arrangement & Location

• Work Mode: Full-time In-Office (5 Days a Week)
• Location: Pune, Maharashtra, India

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