Database Engineering - Lead Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Database Engineering - Lead Engineer based in Mexico.

You will take a senior technical leadership role in designing, building, and operating the data and AI/ML infrastructure powering large-scale, client-facing AI products used by global financial institutions.
This position sits at the core of platform engineering, combining database architecture, cloud infrastructure, and AI/ML systems into a unified production environment.
You will own the end-to-end reliability, performance, and scalability of critical data systems supporting real-time AI applications.
The role involves working across distributed systems, vector search, and cloud-native databases while ensuring high availability and operational excellence.
You will collaborate closely with ML engineers and platform teams to support model serving, retrieval systems, and production pipelines.
This is a highly hands-on leadership role requiring deep technical expertise and the ability to operate in a 24/7 production environment.
You will contribute directly to the evolution of next-generation AI infrastructure powering enterprise-grade financial solutions.

Accountabilities:

• Architect, build, and operate production-grade AI/ML and database infrastructure supporting large-scale AI applications.
• Own the full lifecycle of database systems including OpenSearch, DocumentDB, Aurora PostgreSQL, and Redis across performance, scaling, and disaster recovery.
• Design and implement infrastructure as code using Terraform, Crossplane, and CloudFormation for cloud-native environments.
• Develop and maintain CI/CD pipelines for ML systems, including automated testing and model validation workflows.
• Implement monitoring, logging, and alerting systems using CloudWatch, Grafana, and related observability tools.
• Optimize vector search and embedding systems for retrieval-augmented generation (RAG) use cases.
• Support Kubernetes-based ML workloads including GPU scaling, service mesh, and performance tuning.
• Ensure database security through encryption, IAM policies, TLS configurations, and fine-grained access controls.
• Participate in rotating on-call support for production systems operating in a 24x7 environment.

Requirements:

• 8+ years of experience in platform engineering, infrastructure, or database engineering roles.
• At least 3+ years of hands-on experience in AI/ML infrastructure or production ML systems.
• Strong experience with model serving frameworks such as SageMaker, Bedrock, vLLM, or TGI.
• Deep knowledge of vector databases and search systems, including OpenSearch k-NN indexing and embedding optimization.
• Strong Kubernetes (EKS) experience, including GPU workloads, autoscaling, and distributed system operations.
• Experience designing and operating cloud-native databases such as PostgreSQL, Redis, and document stores at scale.
• Strong understanding of LLM application patterns including retrieval systems, memory management, and agent frameworks (LangChain, LlamaIndex).
• Experience building infrastructure as code using Terraform, CloudFormation, or similar tools.
• Strong expertise in monitoring, observability, and incident response in production environments.
• Solid understanding of database security, encryption, and access control best practices.
• Ability to operate in a high-responsibility, on-call production environment with global coverage requirements.

Benefits:

• Highly competitive compensation package aligned with senior engineering expertise.
• Fully remote working model with structured working hours (Mexico timezone alignment).
• Opportunity to work on cutting-edge AI/ML infrastructure powering global financial institutions.
• Strong culture of ownership, innovation, and technical excellence.
• Comprehensive benefits and rewards program supporting professional and personal well-being.
• Exposure to advanced technologies in AI, machine learning, and large-scale distributed systems.
• Career growth opportunities within a global leader in analytics and decisioning platforms.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1