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ML/AI Ops Engineer
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Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.
About the Role
We’re looking for an ML/AI Ops Engineer with 7+ years of experience to own the end-to-end operationalization of our ML/AI solutions, ensuring models move smoothly from development to scalable, reliable production products. In this role, you’ll design and automate CI/CD pipelines, build and optimize model lifecycle workflows, monitor deployed models for performance, drift, and reliability, and integrate intelligence products into various digital tools such as Copilot, Salesforce, and Tableau. You’ll collaborate closely with Data Scientists, Data Engineers, and Data Architects to transform high-quality research models into robust, production-grade products. This is a key role in shaping a modern ML/AI lifecycle—from CI/CD to high governance.
What You’ll Do
- Own the end-to-end operationalization of ML and AI solutions—from development to scalable, reliable production systemsthat integrateseamlessly with other digital tools.
• Design, automate, and maintain CI/CD pipelines for model training, testing, deployment, and retraining (Azure DevOps, Databricks).
• Build, optimize, and version model lifecycle workflows, ensuring reproducibility, lineage, and governance across the ML/AI platform.
• Monitor production models for performance, drift, reliability, and resource usage; implement automated retraining workflows.
• Optimize compute, storage, and orchestration across the Databricks platform to ensure efficient, cost-effective operations.
• Collaborate closely with ML/AI Scientists, Data Engineers, and DWH team to transform research-grade models into production-ready services.
• Contribute to advancing our ML/AI platform, tooling, automation standards, and best practices.
What You’ll Bring
- Solid experience in operationalizing ML/AI models, including deployment, automation, monitoring, and lifecycle management.
- Strong programming skills in Python,PySpark, and SQL with clean, efficient, production-ready code.
- Experienced in feature engineering with a practical understanding of data engineering fundamentals - designing, validating, and optimizing feature pipelines, and ensuring feature consistency
- Experience in building Vector embeddings & RAG systems.
- Familiarity in ML and LLM models development and libraries used.
- Experience with MLflow (or similar tools) for model tracking, registry management, and lifecycle operations.
- Familiarity with CI/CD pipelines (Azure DevOps preferred)
- Strong grasp of data versioning, model versioning, reproducibility, and data lineage within governed ML/AI environments.
- Experience designing, consuming, or integrating REST APIs to expose ML/AI models as services and support real-time or near-real-time inference.
- Experience monitoring production models, identifying drift or performance issues, and implementing corrective workflows.
- A collaborative, systems-thinking mindset, working closely with ML/AI Scientists, Data Engineers, and Data Warehouse team.
Bonus Skills
- Understanding ofdata quality frameworks and how they integrate into ML pipelines.
- Comfort with infrastructure-as-code for provisioning and managing ML/AI platform components.
- Working knowledge of Unix environments and general DevOps principles; exposure to Docker/Kubernetes is beneficial.
- Experience with real-time or near-real-time serving architectures, event-driven systems, or streaming-based inference.
- Experience with AI agent tools and MCP servers.
- Strong interest in contributing to internal ML/AI platform evolution, including tooling, automation, standards, and best practices.
What You’ll Get
- Two weeks of paid vacation, 12 statutory holidays, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
- Paid parental leave: 8 days for fathers, 122 days for birthing parents, 92 days for adoptive parents
- Medical, dental, and vision coverage fully funded through INS Premium for employees and dependents
- Mental health support, therapy sessions, and virtual care via our Employee Assistance Program
- Retirement and social security contributions through Costa Rica’s statutory programs
- Life insurance equal to 24x monthly salary, plus disability and funeral coverage
- Daily cafeteria subsidy
- Fertility, adoption, and surrogacy support, plus 24 paid volunteer hours through Veeam Cares
- Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events like our annual Global Day of Learning
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The Privacy Notice sets out the basis on which the personal data collected from you, or that you provide to us, will be processed by us in connection with our recruitment processes.
By applying for this position, you consent to the processing of your personal data in accordance with our Recruiting Privacy Notice.
By submitting your application, you acknowledge that the information provided in your job application and any supporting documents is complete and accurate to the best of your knowledge. Any misrepresentation, omission, or falsification of information may result in disqualification from consideration for employment or, if discovered after employment begins, termination of employment.
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Apply to Veeam Software
Important Information
Location: Costa Rica
Work Mode: Hybrid
Job Summary
As a Lead Data Engineer (20627), you will be responsible for designing, developing, and maintaining high-quality software solutions. You will collaborate with cross-functional teams to understand business requirements and translate them into scalable and efficient software applications. Your role will involve leading technical projects, mentoring junior engineers, and continuously improving software development practices to ensure the delivery of robust and reliable software systems.
Responsibilities and Duties
- Lead and mentor a team of data engineers, providing technical guidance, code reviews, and enforcing best practices to ensure high-quality deliverables
- Own and drive the end-to-end data migration strategy from Snowflake on AWS to Azure Databricks and DBT, including planning, execution, and optimization
- Design and oversee scalable, secure, and reliable data pipelines and cloud infrastructure using Azure and infrastructure-as-code practices
- Collaborate with cross-functional stakeholders to align data initiatives with business goals and ensure efficient data integration and transformation
Qualifications and Skills
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience
- 8+ years of experience in Data Engineering, including 2–3 years in a leadership or technical lead role
- Proven experience leading data engineering teams and delivering large-scale data platform initiatives
- Strong hands-on experience with Snowflake, Azure Databricks, and DBT
- Deep expertise in cloud infrastructure and infrastructure-as-code tools, particularly Terraform
- Extensive experience with cloud data migration projects, preferably from AWS to Azure
- Strong experience with CI/CD pipelines and Git-based version control systems
- Advanced proficiency in SQL, data modeling, and ETL or ELT design patterns
- Strong understanding of data architecture, scalability, and performance optimization
- Excellent communication, stakeholder management, and leadership skills, with experience working in insurance or financial data domains
About Encora
Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others.
At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.
Ready to apply?
Apply to EncoraImportant Information
Location: Costa Rica
Work Mode: Hybrid
Job Summary
As a Senior SDET - Data & Analytics (19742), you will be responsible for designing, developing, and maintaining high-quality software solutions. You will collaborate with cross-functional teams to understand business requirements and translate them into scalable and efficient software applications. Your role will involve leading technical projects, mentoring junior engineers, and continuously improving software development practices to ensure the delivery of robust and reliable software systems.
Responsibilities and Duties
- Design and implement end-to-end testing strategies for data pipelines, including dbt models across bronze to gold layers
- Collaborate with data engineers, analytics engineers, and business stakeholders to define testing scope and ensure data quality
- Develop and maintain automated test frameworks, validate ETL processes, and investigate test failures
- Drive continuous improvement in testing practices, processes, and quality standards across the data platform
Qualifications and Skills
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
- 7+ years of experience in Quality Engineering or SDET roles
- Strong experience in data testing, ETL validation, and data warehousing concepts
- Proficiency in SQL and scripting languages such as Python
- Experience with dbt, Databricks, and modern data stack environments
- Strong understanding of testing strategies including the Test Pyramid and automation best practices
- Experience working with version control systems such as Git and collaborative workflows
- Experience in insurance domain with understanding of data models and processes
- Familiarity with BI tools such as Power BI or Tableau and data validation techniques
- Strong communication, analytical, and problem-solving skills with ability to work in Agile environments
About Encora
Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others.
At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.
Ready to apply?
Apply to Encora