AI Engineer

Blackline

Hybrid

Quick summary

Work type: Hybrid
Location: —
Posted: 4 days ago
Closes: Jun 23, 2027

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How this pay compares to similar roles

Similar $204k

$139k most similar roles pay here $258k

This listing doesn't post a salary. Most similar roles pay $161,875–$246,150.

Based on 240 similar postings.

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About Blackline

BlackLine is a cloud-based financial operations management platform that automates and controls the financial close process for enterprises, including account reconciliation, journal entries, and financial reporting. Industry: Financial Technology & Accounting Software

Blackline currently has 20 open roles on FindRole.

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At a glance

TL;DR · AI Engineer

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We are seeking an AI Engineer to join our FinTech SaaS platform team as an early-career professional, combining theoretical expertise in AI/ML with hands-on development skills. In this role, you will collaborate with senior engineers and architects to prototype, validate, and scale customer-facing AI solutions, focusing on generative AI, large language models (LLMs), and agentic systems. Key responsibilities include designing and implementing LLM-based reasoning workflows, retrieval-augmented generation pipelines, and multi-agent orchestration patterns, while also contributing to the establishment of engineering standards for model lifecycle management and security compliance. The ideal candidate holds a Master’s or Ph.D. in Computer Science or Mathematics and has experience with cloud-native AI/ML stacks like Google Cloud Vertex AI, along with hands-on skills in LLM training, fine-tuning, prompt engineering, and multi-agent frameworks.

Skills

Python Google Cloud Vertex AI AWS LLM RAG Multi-agent orchestration MLOps CI/CD

What you'll do

Design and build prototypes of AI-driven solutions based on emerging ideas.
Convert validated prototypes into scalable MVPs ready for production deployment.
Implement components of agentic systems, including LLM-based reasoning workflows.
Evaluate technical feasibility of new business ideas using empirical methods.
Contribute to defining data-driven engineering guidelines for AI solutions.

What we're looking for

Master’s or Ph.D. in Computer Science, Mathematics, or a related field.
2+ years of experience building customer-facing ML or agentic AI solutions.
Strong theoretical grounding in machine learning and generative AI/LLMs.
Hands-on experience with LLM training, fine-tuning, prompt engineering, RAG, and multi-agent orchestration.
Experience with cloud-native AI/ML stacks like Google Cloud Vertex AI.
Innovative problem-solving skills and a customer-focused mindset.
Effective collaboration in cross-functional engineering environments.

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