Senior LLM Orchestration Engineer

Storyful; New York (NY); Hybrid; USD 125,000 - 155,000; Full time

Benefits offered by this job

Healthcare plans

Paid time off

Retirement plans

Education benefits

Wellness resources

Commuter transit program

Subscription discounts

Employee referral program

Financial health programs

Cybersecurity protection

Job summary

Dow Jones invites a Senior Machine Learning Engineer to design and build the core systems behind our production LLM applications, including orchestration, tooling, and evaluation harnesses for trustworthy AI.

You will work with Python, LangChain/LangGraph, and cloud platforms (AWS, Snowflake, Vertex) to create scalable multi-step workflows and agent harnesses while driving observability, latency and cost metrics.

Qualifications

• At least 2+ years’ experience in software/ML engineering with production LLMs.
• Expert Python, hands-on with LLM APIs and cloud platforms (AWS, Snowflake, Vertex).
• Deep experience orchestrating multi-step LLM workflows as execution graphs.

Responsibilities

• Design and build the orchestration, prompting, and workflow layers behind production AI features
• Create composable tools and integrations, including retrieval and MCP servers and clients
• Build evaluators, dashboards, and alerts that track accuracy, latency, cost, and hallucination
• Harden the platform for production scale: caching, reliability, incidents, and model rollbacks
• Set the technical bar through architecture decisions, design reviews, and mentoring

Skills

Python

LLM systems

Prompt engineering

Observability

Mentoring

Explain AI concepts

Tools

LangChain/LangGraph

AWS

Snowflake

Vertex

Claude Code

Job description

Dow Jones invites a Senior Machine Learning Engineer to design and build the core systems behind our production LLM applications, including orchestration, tooling, and evaluation harnesses for trustworthy AI.

You will work with Python, LangChain/LangGraph, and cloud platforms (AWS, Snowflake, Vertex) to create scalable multi-step workflows and agent harnesses while driving observability, latency and cost metrics.