The posting
Our People, Our Core.
At MOOVX, you’ll work alongside curious, talented and collaborative people solving real challenges through technology.
Location: Remote / Hybrid (ARG, CHI, CL, UY, MX)
Job Type: Full-Time
Experience: 5+ years in AI/ML Engineering, Software Engineering, Solution Architecture, or related technical disciplines (1.5+ years in GenAI/LLM).
POSITION SUMMARY
We are seeking a Lead GenAI Engineer to lead the design, development, and deployment of enterprise-grade AI solutions powered by Large Language Models (LLMs), agentic workflows, and Retrieval-Augmented Generation (RAG) architectures.
This role will be responsible for driving the technical vision for scalable GenAI platforms, building intelligent automation solutions, and enabling production-ready AI capabilities across the organization. The ideal candidate has deep expertise in Python development, modern LLM ecosystems, cloud-native architecture, and agent frameworks such as LangGraph, Copilot Studio, or NAAN.
This is a highly visible role requiring both hands-on technical leadership and strategic guidance to help the organization leverage Generative AI responsibly, securely, and effectively.
KEY RESPONSIBILITIES
AI SOLUTION ARCHITECTURE
- Design and implement scalable, secure, and reliable Generative AI architectures for enterprise production environments.
- Define technical standards, reference architectures, and best practices for GenAI platforms and applications.
- Ensure AI solutions meet requirements for performance, observability, scalability, compliance, and governance.
LLM & AGENTIC APPLICATION DEVELOPMENT
- Build and deploy Python-based GenAI services, APIs, and intelligent automation solutions.
- Design and implement agentic workflows using frameworks such as LangGraph, Microsoft Copilot Studio, and NAAN.
- Develop orchestration logic supporting multi-agent and multi-step reasoning workflows.
- Create reusable AI components and frameworks that accelerate solution delivery across teams.
RETRIEVAL-AUGMENTED GENERATION (RAG) & KNOWLEDGE SYSTEMS
- Design and implement RAG architectures that integrate enterprise knowledge sources with LLMs.
- Develop ingestion, indexing, retrieval, and augmentation pipelines for AI-powered applications.
- Integrate and optimize vector databases such as Pinecone, Weaviate, and FAISS.
- Evaluate embedding models and retrieval strategies to improve answer quality, accuracy, and relevance.
CLOUD, DEVOPS & PLATFORM ENGINEERING
- Architect and operate cloud-native AI solutions across AWS, Azure, and/or GCP environments.
- Develop containerized AI applications using Docker and Kubernetes.
- Establish CI/CD pipelines and deployment automation for AI workloads.
- Implement monitoring, logging, observability, and operational controls for production AI systems.
- Ensure platform reliability, scalability, and cost optimization.
INNOVATION & EMERGING TECHNOLOGY EVALUATION
- Evaluate emerging LLMs, agent frameworks, orchestration platforms, and AI infrastructure technologies.
- Recommend tools, platforms, and architectural approaches that align with business and technical objectives.
- Stay current with advancements in Foundation Models, agentic systems, and AI engineering best practices.
- Advocate for responsible AI development, security, governance, and risk management practices.
CROSS-FUNCTIONAL LEADERSHIP
- Partner closely with Product, Engineering, Data, and Business stakeholders to define AI solution roadmaps.
- Provide technical leadership and mentorship to AI and software engineering teams.
- Translate complex business requirements into scalable AI solutions and technical implementation plans.
QUALIFICATIONS
- 5+ years of experience in AI/ML Engineering, Software Engineering, Solution Architecture, or related technical disciplines.
- 1.5+ years of hands-on experience developing and deploying Generative AI or LLM-powered solutions.
- Strong proficiency in Python and modern software engineering practices.
- Experience building production-grade AI services, APIs, and orchestration frameworks.
- Deep understanding of:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Embedding Models
- Prompt Engineering
- Agentic AI Systems
- Hands-on experience with vector databases such as Pinecone, Weaviate, or FAISS.
- Experience developing agent-based solutions using LangGraph, Copilot Studio, NAAN, or similar frameworks.
- Experience designing cloud-native architectures within AWS, Azure, or GCP.
- Familiarity with containerization and orchestration technologies including Docker and Kubernetes.
- Experience implementing CI/CD pipelines and deployment automation.
- Strong communication and stakeholder management skills.
- English: B2+/C1 is a must.
We offer our full-time employees complete and competitive benefits, with a collaborative work environment, competitive compensation, generous work/life opportunities and an outstanding benefits package that includes paid time off plus holidays. In addition, all colleagues are eligible for a number of rewards and recognition programs including billable bonus opportunities. Encouraging a healthy work/life balance and providing our colleagues great benefits are just part of what makes a great place to work.
Ready to make an impact?
If this opportunity feels like the right next step for you, we’d love to get to know you. Apply and show us what you can bring to MOOVX.
We’re committed to building a diverse and inclusive workplace where everyone has the opportunity to grow.
