Gen AI Architech

TeamUp; Monterrey; Presencial; MXN 2.704.000 - 3.425.000; Jornada completa

Descripción de la vacante

TeamUp is seeking a GenAI Architect to design and implement enterprise-grade Generative AI solutions embedded within product platforms. This role bridges AI research, engineering, and product development to ensure scalable, secure GenAI capabilities aligned with business goals. The position requires on-site work in Cleveland, OH, with strict eligibility for U.S.

citizenship or work authorization. You will drive end-to-end GenAI architecture, guide engineering teams, and establish standards for

Formación

• 8+ years in software architecture, ML engineering, or platform engineering.
• 2+ years hands-on with AI/ML systems, including Generative AI.
• Strong software engineering background (Python, Java, or similar).
• Prior work with enterprise AI governance or regulated industries.
• Familiarity with open-source AI ecosystems.
• Background in data platforms or analytics engineering.
• U.S. citizenship or valid U.S. work authorization (visa) — on-site Cleveland, OH.

Responsabilidades

• Design and own the end-to-end architecture for GenAI-powered product features.
• Guide engineering teams on best practices for GenAI development and integration.
• Establish standards and patterns for prompts, agents, and inference layers.
• Ensure security, compliance, and responsible AI principles are built into every solution.

Conocimientos

Generative AI & ML

Foundation models

Prompt engineering

Agent-based frameworks

ML fundamentals

Herramientas

GCP

Kubernetes

CI/CD

Vector databases

Descripción del empleo

Role summary

The GenAI Architect designs, guides, and implements enterprise-grade Generative AI solutions embedded within product platforms. This role bridges AI research, engineering, and product development — ensuring GenAI capabilities are scalable, secure, and aligned with business objectives.

Location & eligibility

• On-site in Cleveland, Ohio (not remote).
• Candidates must be a U.S. citizen or hold a valid U.S. work visa / work authorization .

What you'll do

• Design and own the end-to-end architecture for GenAI-powered product features.
• Guide engineering teams on best practices for GenAI development and integration.
• Establish standards and patterns for prompts, agents, and inference layers.
• Ensure security, compliance, and responsible AI principles are built into every solution.

Core skillset

Generative AI & ML

• Strong understanding of Generative AI models (LLMs, multimodal models, embeddings).
• Hands-on experience with foundation models (GPT-style, Claude-style, LLaMA-style) and model adaptation techniques.
• Expertise in prompt engineering, prompt orchestration, and agent-based frameworks.
• Solid grounding in ML fundamentals: supervised/unsupervised learning, evaluation metrics, inference optimization.

AI architecture & system design

• Design scalable, modular GenAI architectures for production.
• Experience with RAG architectures, vector databases, multi-agent systems, and workflow orchestration.
• Low-latency inference, model routing, and fallback strategies.
• Event-driven, microservices, and API-first architectures.

Product engineering & integration

• Integrate GenAI into customer-facing and internal products.
• Translate product requirements into AI-driven capabilities and technical designs.
• Familiarity with A/B testing, feature flags, and iterative AI product releases.

Data & knowledge engineering

• Data pipelines, feature engineering, unstructured data processing.
• Knowledge graphs, metadata-driven architectures, document ingestion and chunking strategies.
• Data quality, provenance, and governance for AI systems.

Cloud, MLOps & platform

• Strong experience in cloud-native environments (GCP).
• MLOps: model versioning, deployment pipelines, monitoring, logging, drift detection.
• Containerization, Kubernetes, CI/CD.
• Inference optimization and cost-control strategies.

Security, privacy & responsible AI

• AI security risks (prompt injection, data leakage, model abuse).
• Guardrails, content filters, and policy enforcement.
• Responsible AI: explainability, bias mitigation, compliance.
• Familiarity with data privacy regulations (e.g. GDPR) and enterprise governance.

Required qualifications

• 8+ years in software architecture, ML engineering, or platform engineering.
• 2+ years hands-on with AI/ML systems, including Generative AI.
• Strong software engineering background (Python, Java, or similar).
• Prior work with enterprise AI governance or regulated industries.
• Familiarity with open-source AI ecosystems.
• Background in data platforms or analytics engineering.
• U.S. citizenship or valid U.S. work authorization (visa) — on-site Cleveland, OH.