Engineer : Senior LLM Optimization (LLMO) / GEO Expert – Google Vertex

About the Role :

Proso AI is seeking a Senior Expert with hands-on experience in Google Vertex AI to lead short-term projects focused on LLM Optimization (LLMO) and Generative Engine Optimization (GEO) — the next evolution of SEO for the AI era.

You’ll help make sa products and services AI-ready , ensuring they’re discoverable and accurately represented across AI-driven assistants and LLMs like ChatGPT, Copilot, and Gemini.

Key Requirements

Optimize LLM pipelines on Google Vertex AI : Use Vertex AI Prompt Optimizer and Model Optimizer for systematic LLM tuning.

Configure grounding with Google Search or custom data indexes.

Benchmark Gemini and other foundation models for latency, cost, and output quality.

Design RAG (Retrieval-Augmented Generation) workflows : Build and tune hybrid retrieval (keyword + semantic).

Manage vector databases and embeddings (e.g., Vertex Matching Engine, Pinecone, FAISS).

Optimize grounding, citations, and factual consistency.

Implement LLMO & GEO (Generative Engine Optimization) : Create schema-rich, machine-readable content that improves visibility in AI-generated results (Perplexity, ChatGPT, Google AI Overviews).

Collaborate with marketing / data teams to strengthen content discoverability.

Evaluation & A / B Testing : Define success metrics (nDCG, MRR, factual accuracy, latency).

Build continuous evaluation harnesses and dashboards.

Best Practices & Governance : Apply LLM safety guardrails, prompt versioning, and cost-control policies.

Document reusable playbooks and mentor AI / ML engineers.

Required Skills and Experience

3+ years of hands-on experience in AI / ML or NLP engineering , preferably in enterprise or applied research settings.

Proven experience with Google Vertex AI , Gemini models , and Gen App Builder / Vertex AI Search .

Deep understanding of LLM architectures , prompt tuning , RAG , and evaluation metrics .

Experience with Python, Vertex AI SDK, LangChain, Weaviate, Pinecone, or OpenSearch .

Familiarity with LLMO / GEO strategies for AI visibility and structured content optimization.

Strong understanding of GCP architecture , IAM, cost optimization, and API integration.

Excellent analytical, writing, and collaboration skills.

Preferred Qualifications

Background in Computer Science, Data Science, or AI / ML (Bachelor’s or Master’s from a premier institute).

Exposure to Azure AI Search , AWS Kendra , or Elastic / OpenSearch platforms.

Experience building internal AI search, chatbots, or enterprise copilots.

Knowledge of MLOps and Vertex AI Pipelines .

What You’ll Get

Opportunity to work with AI-first founders and global consulting teams .

Access to cutting-edge Google Cloud AI stack and enterprise data systems.

Ownership of real-world GenAI optimization problems in production.

Competitive compensation, fast-track growth, and cross-country exposure (US / UK / EU).

Location : Remote / Noida

Interested candidates can reach out or share their profiles at