Remote AI Engineer for Fintech Data APIs (Go/Python)

Rollbar, Inc.; Detroit (MI); On-site; USD 90,000 - 100,000; Full time

Benefits offered by this job

Fully remote work

Unlimited time off

Job summary

Benzinga seeks an experienced engineer to build AI microservices and production APIs in Go. You’ll take an LLM prototype to a monitored, low-latency endpoint used by paying customers. You own the project end-to-end in a lean team with no handoff.

You’ll ship AI services for summarization, RAG, embedding search, and time series forecasting over financial content, with real-time pipelines on AWS and Kubernetes.

Qualifications

• 4+ years building production AI/ML or data-engineering systems.
• Strong Python, and either Go or solid systems experience with a plan to be productive in Go within a month.
• Hands-on experience deploying LLMs to production (RAG, embeddings, evaluation, context engineering, latency tuning).
• Experience with distributed systems: Kafka, Kubernetes, Postgres, Redis.

Responsibilities

• Build and ship AI services: summarization, RAG, embeddings, event detection, and time series forecasting on financial data.
• Deliver services through low-latency Go APIs for high request volume.
• Design real-time inference pipelines on AWS using Kafka, Kubernetes, and S3.
• Turn unstructured financial text into structured, sellable data.
• Instrument everything: monitoring, drift detection, evaluation, retraining.
• Own deploys: Docker, Kubernetes, ArgoCD, GitLab CI/CD.

Skills

Go

Python

Distributed systems

Kafka

Kubernetes

Postgres

Redis

LLMs in production

Tools

Docker

ArgoCD

GitLab CI/CD

AWS

OpenSearch

Job description

Benzinga seeks an experienced engineer to build AI microservices and production APIs in Go. You’ll take an LLM prototype to a monitored, low-latency endpoint used by paying customers. You own the project end-to-end in a lean team with no handoff.

You’ll ship AI services for summarization, RAG, embedding search, and time series forecasting over financial content, with real-time pipelines on AWS and Kubernetes.