(1609) Senior AI Engineer (Full Stack)
Worldwide | Nov. 13, 2026
Report as Closed
Company:
Nortal
Country: Worldwide
Type: Remote
Employment: Full-time
Description: JoinNortalfor your next big adventure. We areseekinganAI Engineer to design and deliver innovative AI-powered solutions that drive meaningful business impact.
Why joinNortal
- Say Goodbye to Micromanagement:Wechampionautonomy, open communication, and respect for diversity as our core values.
- Outcomes Over Hours:We believe in a work model focused on impact, providing you with the flexibility to balance your professional success with your personal well-being.
- Vibrant Community:Join our close-knit LATAM remote team and connect through tech talks, virtual coffee breaks, and team-building activities.
- Support from Day One:Our People Care team is here to support you throughout your journey, from wellness check-ins to professional growth.
Our benefits✨
- 100% remote work:While you can work from anywhere, you’re always welcome to connect with teammates and grow your network at our coworking spaces across LATAM.
- Paidoff&nationalholidays:Takethetimeyouneedaccordingtoyourcountry’sregulationswhilereceivingyourfullsalary.
- Sick leave:Focus on your health withoutstress. Take the necessary time to recover and feel better.
- Annualcredit:Spenditontheperksyoulovetoenhanceyourwork-lifebalance.
- Team-building activities:Join us for coffee breaks, tech talks, and after-work gatherings to bond with yourNortalfamily and feel part of our vibrant community.
- Birthday off:Enjoy an extra day off during your birthday week to celebrate in style with friends and family.
About the project
As an AI Engineer you’ll take early-stage ideas and rapidly transform them into production-grade applications that empower teams across a global organization. Also , you will architect and develop the Intelligence and Integration Layers that connect autonomous AI agents directly with enterprise systems and infrastructure.
Whatyou’lldo
- Ship End-to-End AI Products: Transform ambiguous business challenges into functional, scalable, and high-performing AI features, applications, and standalone tools.
- Build Persistent & Compliant Memory: Design and implement AI memory architectures and vector stores (such as Pinecone and Pgvector) that preserve contextual information while ensuring compliance with data retention, privacy, and deletion policies.
- Unify Fragmented Enterprise Data: Develop data pipelines and entity-resolution logic to integrate information across CRM, ERP, CPQ, and marketing platforms (such as Salesforce, SAP, and BigQuery), creating reliable, unified data sources that AI agents can leverage.
- Identify High-Value Use Cases: Collaborate directly with business units to understand workflows, identify opportunities for AI-driven improvements, and prioritize use cases that demonstrate measurable value.
- Drive Adoption: Partner with stakeholders throughout development and implementation, ensuring solutions address business needs and are successfully adopted by end users.
- Close the Feedback Loop: Gather and communicate insights from real-world deployments to help engineering and platform teams understand model performance, limitations, and opportunities for improvement.
- Implement EvalOps & Safety Guardrails: Build continuous evaluation pipelines to assess AI models for hallucinations, prompt injections, data leakage, and performance regressions before production deployment.
- Optimize Cost & Latency: Implement semantic caching, intelligent model routing, and inference optimization strategies to reduce response times and operational costs while maintaining solution quality.
What makes you a great fit
5–7+ years of Software Engineering Experience: Strong foundation in backend development, distributed systems, asynchronous programming, API design, microservices, and database managemnt.
2+ years of Production AI / LLM Experience: Hands-on experience designing, developing, and deploying AI-powered applications using LLM APIs, RAG pipelines, and agentic workflows in production environments.
3+ years of Data Engineering & ETL Experience: Proven experience building data pipelines and integrating enterprise systems, including CRM, ERP, CPQ, or marketing platforms. Strong knowledge of data transformation, entity resolution, schema design, and data quality.
3+ years of Python or Equivalent Backend Development: Strong programming skills with the ability to independently develop, integrate, and maintain production-grade AI applications.
1–2+ years of Vector Database & AI Memory Experience: Practical experience with Pinecone, Pgvector, or equivalent technologies for semantic search, contextual retrieval, and persistent AI memory.
1–2+ years of AI Frameworks & Orchestration: Hands-on experience using LangChain, LlamaIndex, or equivalent frameworks to develop RAG systems and agentic AI workflows.
1+ year of AI Evaluation & Safety Experience: Knowledge of AI evaluation pipelines, hallucination detection, prompt injection mitigation, data leakage prevention, and model safety guardrails.
1+ year of AI Performance Optimization: Experience implementing semantic caching, intelligent model routing, inference cost optimization, and latency reduction strategies.
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