Senior llm engineer – training evaluation production deployment and agentic rag

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Amber Stratton

Amber Stratton

ANS Finance

We are seeking a highly skilled Senior LLM Engineer to join our innovative SaaS-based insurance mining platform. We have experienced record growth and are excited to grow the team. The ideal candidate will have industrial real world production expertise in fine-tuning large language models (LLMs), deep learning, and retrieval-augmented generation (RAG). This role requires hands-on experience with containerized workflows (e.g., Docker), Azure cloud services, and LLM optimization tools such as Unsloth, Lora and Qlora. You will be responsible for building, optimizing, and deploying models with large context windows to drive value for our insurance clients.

This is direct hire role only no third parties or agencies.

Candidates from Argentina, Pakistan and India encouraged to apply

All Candidates will be required to take an automated test, followed by white board session.

Candidate must be fluent to the highest level in written and spoken English language.

This is a fully remote position.

In order to be considered for this role:

Candidate must have at least 4 years of experience with title ML Engineer or Data Scientist.

Candidate must have 2 years continuous employment with the same employer

Candidates must have completed a Stem related degree (not have one in progress)

Recent grads are NOT a fit for this role.

Key Responsibilities:

1. Model Development & Fine-tuning:

Fine-tune and deploy large-scale LLMs (e.g., GPT, OPT, Llama, Falcon,Qwen) to extract insights from structured and unstructured insurance data (e.g., policy documents, claims data).

Candidate must have experience with agentic AI with preference on Langchain/Langsmith

Leverage transfer learning and parameter-efficient fine-tuning (LoRA, PEFT) to optimize performance for specific tasks, such as document summarization and claims processing.

Implement large-context-window models to h