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Day 60
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From 51 similar postings that came down. Coming down is not always a hire.
Los Angeles HQ · Culver City, California, USA
Live, first seen by us 60 days agoEmployment type: Full-timeFrom the employer’s posting
Department: Data ScienceFrom the employer’s posting
Build and own the internal AI platform: agent harness, MCP servers, tool integrations
Embed with Finance, Sales Ops and Compliance to map how their work happens
Ship systems that replace manual workflows and hand them off to those teams
Extend data infrastructure: DBT models, BigQuery, orchestration, production pipelines
Share ownership of monitoring, alerting, and data reliability
Building and owning our internal AI platform: the agent harness, MCP servers and tool integrations
Embedding with Finance, Sales Ops, Compliance, and onboarding to understand how their work actually happens
then shipping the systems that replace the manual version and handing them off to those teams
Extending our data infrastructure alongside our Staff Data Engineer: DBT models, BigQuery, orchestration, and the production pipelines
Sharing ownership of monitoring, alerting, and data reliability for the systems that unblock product launches
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 60
Similar jobs usually come down between day 4 and day 77.
From 51 similar postings that came down. Coming down is not always a hire.
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- You've built with LLM APIs, agent frameworks, and MCP in production, beyond prompting, and you know what belongs in code versus a model - Strong fundamentals in TypeScript/Node or Python and the willingness to work in both, plus fluency with a cloud data warehouse such as BigQuery, Snowflake, or Databricks - You can sit with a non-technical team, understand how their work actually happens, and come back with a system
- Embedding with Finance, Sales Ops, Compliance, and onboarding to understand how their work actually happens, then shipping the systems that replace the manual version and handing them off to those teams - Extending our data infrastructure alongside our Staff Data Engineer: DBT models, BigQuery, orchestration, and the production pipelines - Sharing ownership of monitoring, alerting, and data reliability for the systems that unblock product launches
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New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Lightspark is creating the Money Grid, modern, open financial infrastructure that makes payments accessible, affordable, and instant for businesses and users worldwide. We're challenging the status quo, updating the current system, and empowering our partners to build better solutions. Together, we're building the most advanced financial infrastructure, open, instant, and global, inspiring a future where anyone, anywhere can access the full potential of digital money.
We are looking for engineers who enjoy building and shipping quickly, learning how other teams work, and seeing their work change how an entire company operates. As a Senior Software Engineer on the Data & AI team, you'll expand Lighthouse, our internal data and AI platform, into the layer that lets every function at Lightspark run on trusted data and AI agents.
Most of the value in applied AI comes from the connective work: wiring models to a company's data, its tools, and the way people actually work, then getting the result adopted. We've built that layer for analytics, where Lighthouse now handles most of what our team used to do by hand and is used across the company. This role extends it to Sales, Finance, Ops, Legal, Compliance, and Partnerships: the agent harness, tool integrations, governed source-of-truth data, and the execution layer those teams run their workflows on. General-purpose assistants get partway there and miss things; you'll build the structure underneath so the answers are right, repeatable, and owned by the teams that need them.
You'll work on a small, senior team with a lot of ownership. Problems come from talking with the teams you support rather than from a spec; you'll scope them, ship the solution, and make sure it sticks.
WHAT YOU'LL BE DOING
Building and owning our internal AI platform: the agent harness, MCP servers and tool integrations, context and access services, sandboxed execution, and cost and usage tracking
Embedding with Finance, Sales Ops, Compliance, and onboarding to understand how their work actually happens, then shipping the systems that replace the manual version and handing them off to those teams
Extending our data infrastructure alongside our Staff Data Engineer: DBT models, BigQuery, orchestration, and the production pipelines
Sharing ownership of monitoring, alerting, and data reliability for the systems that unblock product launches
Partnering with Engineering to optimize their own dev systems and tooling
WHAT WE'RE LOOKING FOR
4+ years experience shipping and maintaining production systems; data engineering, ML engineering, and backend/full-stack backgrounds all fit
You've built an internal platform or workflow system that other teams adopted, not just features on top of one
You've built with LLM APIs, agent frameworks, and MCP in production, beyond prompting, and you know what belongs in code versus a model
Strong fundamentals in TypeScript/Node or Python and the willingness to work in both, plus fluency with a cloud data warehouse such as BigQuery, Snowflake, or Databricks
You can sit with a non-technical team, understand how their work actually happens, and come back with a system
Comfortable working with ambiguity in a startup environment
Experience in payments, crypto, or blockchain is a plus, but not required
Based in LA or Openness to relocate to Los Angeles, California
This is not an ML infrastructure, model-training, or prompt-engineering role. You might currently be an AI engineer, ML engineer, data engineer, or full-stack engineer who has spent the last year or two building agents and internal tooling. If you don't match every line above but have built systems like these, we'd like to hear from you.
Lightspark is on a mission to build the future of open, instant, and global financial infrastructure making payments accessible and affordable for everyone, everywhere. We're committed to creating a more inclusive and diverse workplace to reflect the customers we serve. We welcome interest from individuals of all backgrounds and levels of experience who share our mission. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other applicable legally protected characteristics.
For US Applicants:
We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the State of California Fair Chance Initiative for Hiring.
For EU Applicants:
In accordance with applicable EU and local regulations, including the Estonian Employment Contracts Act, Equal Treatment Act, and Gender Equality Act, Lightspark ensures equal treatment throughout the hiring process.
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Culver City, California, USA
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