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 yukti.taneja@proso.ai