Ofertas de empleo para Desarrollo de Software en Alicante/Alacant

• Nivel de experiencia---
• Tipo de contratoA tiempo completo
• PublicadaNueva

. Python Azure Docker Cloud Coumputing Kubernetes AWS DevOps

We’re looking for an AI Engineer to join our growing Data & AI team. This role focuses on building and scaling the platform behind AI products, ensuring they run reliably, efficiently, and at scale.

This position is strongly focused on platform, infrastructure, automation, observability, and operations rather than on building ML models or AI products themselves.

You will work with modern cloud technologies (mainly AWS, with some Azure exposure) and collaborate closely with Data Scientists, Data Engineers, and Product teams to bring AI solutions into production and keep them running smoothly.

We are open to candidates with strong expertise in at least one core area (e.g. cloud, DevOps, platform engineering, or ML operations) and solid foundational knowledge in the others, with motivation to grow across the full AI operations stack.

What You’ll Do

• Design, build, and evolve our AI operations platform
• Operate and optimize ML and LLM pipelines (RAG, agents, etc.)
• Ensure reliability, scalability, and observability of AI systems
• Monitor model performance, quality, and drift
• Manage deployments in AWS/Azure with Docker & Kubernetes
• Implement LLMOps / AgentOps practices (evaluation, logging, orchestration)
• Drive automation, CI/CD, and infrastructure as code
• Partner with cross-functional teams to bring AI solutions into production
  
  

What We’re Looking For

• Experience in MLOps, AIOps, or operating ML systems in production
• Strong background in cloud (AWS and/or Azure)
• Hands-on with Docker, Kubernetes, and CI/CD pipelines
• Experience with monitoring & observability tools
• Knowledge of LLMs, RAG pipelines, or AI agents
• Solid Python skills and understanding of ML lifecycle
  
  

Nice to have

• Experience with tools like SageMaker, Azure ML, MLflow, Kubeflow
• Familiarity with LangChain, LlamaIndex or similar frameworks
• Exposure to speech analytics or conversational AI
• Experience with workflow orchestration tools (Airflow, Argo, etc.)
  
  

About Verisure

At Verisure, we do something amazing every day. By protecting what matters most, we change lives for the better. We are the leading provider of professionally monitored security services with 24/7 response in Europe and Latin America. More than 6 million families and small businesses in 18 countries rely on our innovative technology to protect what matters most to them.

We integrate product development, design, sales, installation services and a 24/7 professional monitoring solution. We have a track record of continuous growth, as well as exciting plans to continue expanding, transforming, and leading the market into the future.

Our success depends on our people, and we invest in them every day. Working with Verisure is being part of an industry-leading, world-class company that has a strong entrepreneurial spirit.

Strong Fit With Our Company DNA

• Passionate in Everything We Do: Our people have a sense of energy that is unmistakable, one that drives us to delight our customers and focus on creating impact quickly.
• Committed to Making a Difference: When we say we will do something; we deliver with excellence. We are accountable, focused and operate with discipline.
• Always Innovating: We believe that Innovation can be big or small; it’s a continuous state of mind that inspires us to think differently and always make things better.
• Winning as a Team: Our people know that by leveraging one another’s strengths, investing in and developing our team’s capability and by collaborating well, we will win.
• With Trust & Responsibility: Operating with integrity is core to our success. We are humble, honest and value deep mastery and expertise. We do the right thing, always.
  
  

Diversity, inclusion, equity, and belonging at Verisure

At Verisure, we are committed to fostering a diverse and inclusive workplace, recognising that diversity of thought and background only makes our teams stronger and more innovative. We reject all forms of discrimination and bias, and we believe in access to opportunities for everyone, regardless of gender, age, disability status, race, sexual orientation, or any other status.

Apply today!

We are continuously reviewing candidates, so we encourage you to apply as soon as you can. If you have questions regarding this position, please reach out to our Group TA Specialist, Elvira Torres at [email protected]

• Nivel de experiencia---
• Tipo de contratoA tiempo completo
• PublicadaNueva

. Python Azure Jenkins Docker Cloud Coumputing Kubernetes AWS DevOps Terraform Machine Learning

We are looking for a MLOps / AIOps / LLMOps / AgentOps Engineer to join a multidisciplinary Data & AI team. The main mission of this role is to design, operate, and continuously evolve our AIOps platform, ensuring that our AI products run in a reliable, scalable, and cost‑efficient way.

This position is strongly focused on platform, infrastructure, automation, observability, and operations rather than on building ML models or AI products themselves.

You will work with modern cloud technologies (mainly AWS, with some Azure exposure) and collaborate closely with Data Scientists, Data Engineers, and Product teams to bring AI solutions into production and keep them running smoothly.

We are open to candidates with strong expertise in at least one core area (e.g. cloud, DevOps, platform engineering, or ML operations) and solid foundational knowledge in the others, with motivation to grow across the full AI operations stack.

Key Responsibilities

• Design, maintain, and evolve the AIOps platform supporting:
• Traditional machine learning models in production
• LLM‑based solutions such as RAG pipelines and AI Agents
• Speech Analytics use cases (ASR, conversation analysis, NLP)
• Build and operate ML and LLM pipelines with a strong focus on:
• Reliability, automation, and observability
• Model and LLM quality, performance, and drift monitoring
• Cloud cost control and optimization
• Implement LLMOps / AgentOps practices, including:
• LLM evaluation and observability
• Prompt management, traceability, and specialized logging
• Agent integration, orchestration, and lifecycle management
• Ensure continuous operation of AI products, including:
• Alerts, dashboards, SLOs / SLIs
• Scalability strategies and basic auto‑remediation mechanisms
• Manage deployments in cloud environments (AWS / Azure) and container platforms (Docker / Kubernetes)
• Collaborate closely with Data Scientists and Data Engineers to productionize robust, scalable AI solutions
• Contribute to internal standards, automation, and best practices across the AI and data ecosystem
  

Required Skills (Must Have)

• Hands‑on experience in MLOps, AIOps, or operating ML systems in production
• Solid understanding of LLMOps and AgentOps concepts (RAGs, agents, evaluation, monitoring)
• Experience working with AWS and/or Azure in production environments
• Practical knowledge of containers and Kubernetes (Docker, basic Helm usage, etc.)
• Experience with CI/CD pipelines (GitHub Actions, GitLab CI, Azure DevOps, Jenkins, or similar)
• Familiarity with observability and monitoring concepts (CloudWatch, OpenTelemetry, Prometheus, etc.)
• Experience managing infrastructure as code (Terraform, Bicep, CDK, or similar)
• Python experience and familiarity with the ML ecosystem (e.g. scikit‑learn, PyTorch), even if not a Data Scientist
• Good understanding of the ML / LLM lifecycle, from development to production and monitoring
• Fluent English to work in an international environment
  
  

Nice To Have (Not Required, But Valuable)

• Experience with ML/AI platforms such as SageMaker, Azure ML, MLflow, Kubeflow
• Exposure to Speech Analytics technologies (ASR, diarization, conversational NLP)
• Experience with cloud cost optimization / FinOps, especially for AI workloads
• Experience building or operating AI agents, copilots, or conversational systems
• Familiarity with LLM frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.)
• Experience with workflow and orchestration tools (Airflow, Argo, Step Functions, Durable Functions)
  
  

Professional Skills & Mindset

• Strong focus on reliability, automation, and scalability
• Ability to collaborate effectively in multidisciplinary teams
• Clear communication and documentation‑oriented mindset
• Platform mindset: building reusable, maintainable, and robust solutions
• Proactive, analytical, and continuous‑improvement driven
• Strong sense of ownership and end‑to‑end responsibility
• Motivation to learn and grow across the AI operations stack
  
  

Technology Environment

• Cloud: AWS, Azure
• Orchestration & Containers: Kubernetes, Docker
• CI/CD: GitHub Actions, GitLab CI, Azure DevOps
• Observability: Prometheus, Grafana, ELK/EFK, OpenTelemetry
• Infrastructure as Code: Terraform, Bicep, CloudFormation
• AI / ML Tools: MLflow, Azure ML, SageMaker, LangChain, LlamaIndex, Semantic Kernel
• Primary Language: Python