Senior AI Engineer: Grounded ML & LLM Systems for Finance

MeeruAI; Pleasanton (CA); On-site; USD 140,000 - 230,000; Full time

Job summary

Meeru AI is seeking a Senior AI Engineer to build the AI and intelligence layer with strict grounding and auditable outputs. You’ll develop customer-specific models, a guarded NLG layer, and orchestration systems, working closely with evaluation engineers to ensure fidelity to verified data.

The role requires hands-on production Python work, access to data warehouses, and deployment in customer environments.

Qualifications

• Experience building per-customer ML models using time-series and operational data.
• NLP generation must be strictly grounded in verified data with guardrails.
• Implement verification checkpoints in CI to gate grounding and faithfulness.

Responsibilities

• Build per-customer ML models learning normal vs. anomalous behavior.
• Design a template-first grounded NLG layer with guardrails and structured output.
• Implement agentic orchestration with verification and human-confirmation checkpoints.
• Integrate managed LLMs running in customer clouds (Bedrock, Vertex AI, Azure OpenAI).
• Collaborate with an evaluation engineer to gate grounding and faithfulness checks in CI.
• Turn user feedback into durable model and system improvements.
• Deliver production Python services with SQL/warehouse access (Snowflake, PostgreSQL) in containerized deployments.

Skills

ML model development

Grounded NLG

Agent orchestration

LLM integration

CI validation

Python production services

Tools

LightGBM

XGBoost

Snowflake

PostgreSQL

LangGraph

AWS Bedrock

GCP Vertex AI

Azure OpenAI

Docker

Job description

Meeru AI is seeking a Senior AI Engineer to build the AI and intelligence layer with strict grounding and auditable outputs. You’ll develop customer-specific models, a guarded NLG layer, and orchestration systems, working closely with evaluation engineers to ensure fidelity to verified data.

The role requires hands-on production Python work, access to data warehouses, and deployment in customer environments.