Data & AI Architects

Genesis Consulting Partners, LLC; Brasil; Presencial; BRL 300 000 - 540 000; Tempo integral

Resumo da oferta

Genesis Consulting seeks experienced Data & AI Architects to define and deliver scalable data and AI architectures across diverse industries. You will translate business challenges into technical roadmaps, guide POCs to production-ready solutions, and lead cross-functional teams in creating measurable business value.

The role emphasizes connecting data strategy with AI capabilities, governance, and secure, scalable deployment across cloud environments, with opportunities to shape advisory

Qualificações

• Proven experience in data/AI architectures and related fields in large-scale environments.
• Strong knowledge of Generative AI, LLMs, RAG, embeddings, and AI-based architectures.
• Advanced ML/DL expertise including model evaluation and optimization techniques.
• Familiarity with modern data architectures: data lakes, lakehouses, data warehouses, and data pipelines.

Responsabilidades

• Design modern Data & AI architectures including lakes, warehouses, pipelines, governance, and security.
• Assess client environments, identify gaps, and propose scalable modernization opportunities.
• Translate business goals into technical architectures connecting data and AI capabilities.
• Define use cases, prerequisites, roadmaps, and ROI for Data & AI initiatives.
• Evaluate technologies and architectures for cost, performance, and time-to-market.
• Provide technical leadership for POCs, MVPs, and Data & AI solutions.

Conhecimentos

Data Architecture

AI Architecture

Data Engineering

Machine Learning

Generative AI

LLMs

RAG

AI agents

embeddings

Vector Databases

Data Lakes

Lakehouses

Data Warehouses

Cloud AWS/Azure/GCP

CI/CD

MLOps/LLMOps

Observability

Monitoring

Git

Containers

Formação académica

Bachelors in CS/Engineering/Stats/Math/IS

MBA / Master’s in Data/AI/Tech/Business

Descrição da oferta de emprego

Genesis Consulting is seeking experienced Data & AI Architects with a strong strategic and technical vision, a genuine passion for technology, and a focus on delivering business value. Our clients include some of the world’s leading companies across different industries, and the professional will be part of challenging projects, contributing to the definition of Data & AI architectures, the design of scalable solutions, and the transformation of business challenges into concrete technology initiatives.

The professional will be responsible for connecting business strategy, data, artificial intelligence, and technology architecture by assessing clients’ current environments, identifying opportunities, and defining solutions that can evolve from Proofs of Concept (POCs) into production-ready products and solutions.

Duties and Responsibilities

• Design modern Data & AI architectures, considering data lakes, lakehouses, data warehouses, data pipelines, data integration, governance, security, and Analytics and AI platforms;
• Assess clients’ existing architectures and technology environments, identifying gaps, modernization opportunities, and improvements in scalability, performance, security, and governance;
• Translate strategic objectives and business challenges into technical architectures and solutions, establishing the connection between data, AI capabilities, and expected business outcomes;
• Identify, structure, and scope Data & AI use cases, defining objectives, deliverables, assumptions, data and technology prerequisites, complexity, roadmap, effort estimates, and potential business impact and ROI;
• Evaluate and select technologies, frameworks, and architectures for solutions involving Generative AI, LLMs, AI agents, RAG, Machine Learning, Deep Learning, and Advanced Analytics;
• Provide technical leadership in the conception and development of POCs, MVPs, and Data & AI solutions, ensuring that solutions are technically feasible, scalable, and aligned with business objectives;
• Define architectures and best practices for the development, deployment, and operation of Machine Learning models and AI solutions, including MLOps, LLMOps, CI/CD, observability, and monitoring principles;
• Incorporate software engineering principles, including modularity, automated testing, version control, documentation, architectural patterns, code quality, and process automation;
• Define governance, security, privacy, and access control strategies for data environments and AI solutions, considering corporate and regulatory requirements;
• Work closely with business, technology, data, and engineering stakeholders, acting as a bridge between business needs and technical decisions;
• Produce architectures, diagrams, technical specifications, roadmaps, and other artifacts required to guide solution implementation;
• Support clients in defining Data & AI roadmaps, prioritizing initiatives based on business value, technical feasibility, data availability, and implementation effort.

Minimum Qualifications / Experience

• Proven experience working in Data Architecture, AI Architecture, Data Engineering, Machine Learning, or related fields, preferably in large-scale enterprise environments;
• Extensive knowledge of Generative AI, Large Language Models (LLMs), RAG, AI agents, embeddings, Vector Databases, and AI-based application architectures;
• Advanced knowledge of Machine Learning and Deep Learning, including supervised and unsupervised models, time series, model evaluation, and optimization techniques;
• Strong knowledge of modern data architectures, including Data Lakes, Lakehouses, Data Warehouses, distributed architectures, data pipelines, and Analytics platforms;
• Experience with cloud computing platforms and data and AI services from at least one of the major providers: AWS, Azure, or GCP;
• Knowledge of modern software engineering practices, including application architecture, APIs, microservices, Git, CI/CD, automated testing, containers, and software development principles;
• Knowledge of MLOps/LLMOps, including model training and deployment, model serving, monitoring, observability, versioning, and model governance;
• Ability to evaluate technologies and make architectural decisions considering trade-offs involving cost, performance, scalability, security, governance, and time-to-market;
• Experience structuring POCs and MVPs, from problem definition and scoping through architecture, implementation, and results evaluation;
• Ability to understand business problems and translate them into use cases, technical requirements, deliverables, and success metrics, including feasibility assessment and potential return on investment;
• Excellent communication skills, with the ability to present technical concepts to executive audiences and work effectively with multidisciplinary teams;
• Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, Information Systems, or related fields;
• A postgraduate degree, MBA, or Master’s degree in Data, AI, Technology, or Business-related fields will be considered a plus.