AI Engineer – SaaS Platform

Job not on LinkedIn

🕒 May 23

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Marrina Decisions

WebsiteLinkedInAll Job Openings

11 - 50 employees

🤝 B2B

B2B • Marketing

Marrina Decisions is a marketing services company that specializes in managed services for marketing campaigns, particularly those involving Marketo. They offer a wide range of services including Marketo optimization, migration, and quick launch, as well as email marketing services. The company acts as an extended team to offload marketing campaign execution work, allowing businesses to focus on their core activities. With expertise in marketing automation and operations, Marrina Decisions prides itself on delivering high-quality, efficient, and empathetic services that make a measurable impact on their clients' campaigns. Clients commend their ability to seamlessly integrate and manage multi-channel and multi-product customer journeys.

📋 Description

• Maintain and optimize LLM- and VLM-powered services for content generation, compliance scoring, and campaign testing. • Manage and scale Flask/FastAPI microservices, ensuring high uptime and low latency. • Maintain Dramatiq queues for async AI workflows, campaign generation, and pipeline orchestration. • Deploy, monitor, and debug Uvicorn/Gunicorn-based hosting in production environments. • Integrate with OpenRouter and equivalent LLM routing tools to balance cost, latency, and quality. • Design and refine prompt engineering strategies for reliability, context-awareness, and compliance. • Build and maintain feedback pipelines for AI model evaluation (human-in-the-loop scoring, automated quality checks, reinforcement). • Expose and maintain REST APIs for AI services, ensuring secure, versioned endpoints. • Collaborate with backend/frontend teams to keep microservice architecture aligned and maintainable. • Track token consumption, latency, and error rates to ensure production-grade performance.

🎯 Requirements

• 3–5 years as an AI Engineer or Python Backend Engineer working with production systems. • Strong in Python, with experience in production-grade codebases. • Flask (for APIs), FastAPI (optional), Uvicorn/Gunicorn for async hosting. • Dramatiq (or Celery/RQ equivalent) for background jobs. • Hands-on with LLMs and VLMs, including prompt engineering, fine-tuning, and evaluation. • Familiar with OpenRouter or equivalent LLM/VLM routing & fallback tools. • Experience designing and maintaining microservice architectures. • Strong experience with REST API design (auth, rate limiting, documentation). • Dockerized deployments, CI/CD pipelines, logging/monitoring, error handling. • Building structured evaluation/feedback systems for AI model performance. • AWS/GCP experience preferred (deployment, monitoring, scaling).