5 melhores vagas de observability specialist para lisboa, p11 (Contratando agora!)

AI Architect
Inetum Portugal —Lisboa
- Período Integral
- Modelo Híbrido
Candidatura rápida
Data Engineer Senior
Inetum Portugal —Lisboa
- Período Integral
- Modelo Híbrido
Candidatura rápida
Senior Data Engineer - Product
Feedzai —Lisboa
- Teletrabalho
Senior AI DevOps / LLMOps
TechBiz Global GmbH —Lisboa
- Período Integral
- Teletrabalho
- Graduação
Candidatura rápida
Cloud Application Operations Engineer
Shield —1990 Lisboa
- Período Integral
- Modelo Híbrido
Candidatura rápida

More jobs to discover

Find similar jobs that you might be interested in.

Senior Software Engineer
Logicalis —Lisboa
Conhecimento na implementação de soluções on premises, híbridas e cloud, com boas práticas de segurança, observabilidade e integração com sistemas existentes;

Quero receber o alerta de ofertas mais recentes para observability specialist em lisboa, p11

Ao iniciar sessão na sua conta, concorda com os Termos de Serviço do SimplyHired e consente com a nossa Política de Privacidade e Cookies.

AI Architect

Inetum Portugal -
Lisboa

Candidatura rápida

Detalhes da oferta

Período Integral

Descrição completa da oferta

Company Description

Inetum is a European leader in digital services. Inetum’s team of 28,000 consultants and specialists strive every day to make a digital impact for businesses, public sector entities and society. Inetum’s solutions aim at contributing to its clients’ performance and innovation as well as the common good.

Present in 19 countries with a dense network of sites, Inetum partners with major software publishers to meet the challenges of digital transformation with proximity and flexibility.

Driven by its ambition for growth and scale, Inetum generated sales of 2.5 billion euros in 2023.

Job Description

The Senior AI Architect will be responsible for defining the technological vision and leading the implementation of next‑generation Artificial Intelligence architectures. This role combines deep technical expertise, strategic thinking, and strong business alignment, ensuring that AI/GenAI solutions are scalable, secure, and deliver real impact.

Key Responsibilities

Architecture & Strategy

Design the target architecture for AI ecosystems, including Copilots/Agents, Azure OpenAI, AI Search, data platforms, integrations, and pipelines, ensuring end‑to‑end alignment with customer objectives.
Define technical standards, guardrails, security practices, domain blueprints, and architectural guidelines, ensuring cross‑organizational consistency.
Translate business needs into structured technical solutions, leading workshops, discovery sessions, and technical assessments.
Assess trade‑offs between performance, cost, risk, and complexity when defining AI/GenAI solutions.

Technical Design & Implementation

Lead the design of scalable, secure, high‑performance AI/GenAI architectures.
Select the appropriate technologies, frameworks, and models (LLMs, RAG, vector DBs, multi‑agent systems, MLOps, automation tooling).
Build and validate PoCs and reference architectures to accelerate AI adoption.
Integrate models, agents, and data pipelines with APIs, microservices, core business applications, and enterprise data sources.

Governance, Quality & Security

Establish principles for technical security, data isolation, compliance, observability, and model governance.
Ensure adherence to best practices in performance, resilience, scalability, and privacy.
Define mechanisms for control, auditability, and continuous improvement of AI architectures in production.
Work closely with IT and Security teams to ensure consistent integration with the customer’s enterprise architecture.
Ensure architectural consistency across multiple AI use cases and domains, particularly in large‑scale AI programs.

Technical Leadership & Collaboration

Act as a technical authority for internal and external stakeholders, including Data, Engineering, Product teams, and C‑level leadership.
Mentor Data Scientists, ML Engineers, and Software Engineers, promoting technical excellence and best practices.
Support pre‑sales, RFPs, solution proposals, and technology vision for strategic clients.

Qualifications

6–10 years of experience in software development, solution architecture, data engineering, or AI.
Solid experience in AI/ML and GenAI, including LLMs, pipelines, RAG, and enterprise integration.
Strong knowledge of ML frameworks such as TensorFlow, PyTorch, Scikit‑learn.
Significant experience with Azure (preferred), AWS or GCP, CI/CD, Docker/Kubernetes, and microservices.
Strong understanding of AI‑related security, cloud architectures, and MLOps practices.
Excellent communication skills, both technical and non‑technical.
Proven experience in technical leadership and architectural standards definition.

Additional Information

Experience in technology consulting and client interaction.
Certifications such as Azure AI Engineer / Solution Architect, AWS ML Specialist, Google Cloud ML.
Knowledge of architecture frameworks: TOGAF, DDD, Clean Architecture, SAFe.
Participation in conferences, talks, or thought leadership initiatives.

Candidatura rápida

Refine sua pesquisa

observability specialist vagas para: lisboa, p11

AI Architect

Data Engineer Senior

Senior Data Engineer - Product

Senior AI DevOps / LLMOps

Cloud Application Operations Engineer

More jobs to discover

Quero receber o alerta de ofertas mais recentes para observability specialist em lisboa, p11

Related Searches

Ferramentas para Candidatos

Ferramentas da empresa

Procurar

Mantenha-se em Contacto