Job Overview
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Job Description
About Lumenalta
Lumenalta partners with forward-thinking organizations to build scalable technology solutions that delight users and accelerate business growth. Our global teams prioritize curiosity, commitment, and technical excellence, empowering every member with transparency, autonomy, and impact to do their best work.
The Opportunity: AI Engineer
We are seeking experienced AI Engineers to join a high-growth fintech prospect focused on back-office workflow automation. This role offers the chance to design and deploy production-grade AI systems for community banks, mortgage, and insurance institutions, while shaping a flexible, modern architecture alongside an an accomplished executive team.
What You’ll Be Doing
- Design, build, and deploy AI models into production, moving beyond prototypes and wrappers.
- Develop and maintain backend Python services that power intelligent automation workflows.
- Implement enterprise-scale data pipelines for ingesting and processing financial and regulatory documents, including automated data quality checks and monitoring.
- Train and optimize models on banking rules, compliance standards, and regulatory datasets.
- Build intelligent routing systems, such as auto-approval for simple loans/accounts and escalation to humans for complex cases.
- Collaborate with engineering leadership to shape architecture, delivery models, and stack decisions.
- Ensure compliance-first design, embedding regulatory considerations into every product feature.
What We’re Looking For
- Experience: 3–5+ years in AI/ML engineering with a track record of deploying AI into production at scale.
- Technical Skills: Strong backend Python; expertise with ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.); familiarity with modern data pipeline tools (Airflow, Spark, Kafka) and workflow orchestration frameworks such as n8n or LangGraph.
- Applied AI: Background in enterprise applications such as chatbots, workflow automation, RAG pipelines, or intelligent document processing.
- Domain Awareness: Understanding of regulated industries (financial services, insurance, or similar) with the ability to design compliance-aligned models.
- Collaboration: Comfortable working with a lean, high-performing team and influencing technical direction.
- Adaptability: Excels in startup-like environments with flexible, evolving tech stacks.
Why Lumenalta is an amazing place to work at
At Lumenalta, you can expect to:
- Be 100% dedicated to one project at a time, fostering innovation and growth.
- Be part of a team of talented and friendly senior-level developers.
- Work on projects that leverage leading-edge technology.
Location & Work Arrangement
This is a fully remote position open to candidates based in Latin America (LATAM). While location is flexible, candidates must be willing to maintain at least a 6-hour overlap with core business hours, which are primarily aligned with the Pacific, Central, or Eastern U.S. time zones to ensure effective collaboration with project teams.
Application Details
This role is an evergreen position with no predetermined start date. Applications will be accepted until March 29, 2026. The position may be reposted to allow us to connect with additional qualified professionals as we build our talent pipeline.
Key skills/competency
- AI/ML Engineering
- Production Deployment
- Backend Python
- Machine Learning Frameworks
- Data Pipelines
- Workflow Automation
- Fintech Domain
- Regulatory Compliance
- RAG Pipelines
- Intelligent Document Processing
How to Get Hired at Lumenalta
- Research Lumenalta's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume for AI Engineer roles: Highlight experience deploying AI to production, Python expertise, and regulated industry knowledge.
- Showcase your AI/ML projects: Prepare to discuss applied AI experience like RAG pipelines or workflow automation during interviews.
- Understand fintech and compliance: Demonstrate domain awareness in financial services and regulatory compliance in your application materials.
- Prepare for technical and behavioral questions: Be ready to discuss Python, ML frameworks, data pipelines, and your collaborative approach.
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