Sr. Database Administration

Company Profile: 

ProductSquads was founded with a bold mission: to engineer capital efficiency through 
autonomous AI agents, exceptional engineering, and real-time decision intelligence. We’re 
building an AI-native platform that redefines how software teams deliver value—whether 
through code written by humans, agents, or both. Our stack combines agentic AI systems, ML 
pipelines, and high-performance engineering workflows. This is your chance to build not just

models, but systems that think, decide, and act. We’re developing AI fabric tools, domain- 
intelligent agents, and real-time decision systems to power the next generation of product delivery.

Job Summary: 

The Senior Database Engineer is responsible for designing, managing, and modernizing scalable 
and secure database platforms. The role focuses on reliability, performance, cloud migration, 
automation, and AI-assisted operations while collaborating with engineering teams to support 
production systems and ensure high availability and operational excellence. 

Key Responsibilities: 

Database Engineering & Operations 
• Design, implement, and operate relational and non-relational database platforms supporting business critical applications. 
• Ensure high availability, backup, restore, and disaster recovery across production and non- production environments. 
• Lead performance tuning, capacity planning, and reliability improvements. 
Cloud & Platform Modernization 
• Engineer and operate cloud-native and hybrid database solutions. 
• Execute database migrations and platform modernization initiatives. 
• Apply infrastructure-as-code and repeatable patterns for database provisioning and change.

Evaluation, Safety, and Reliability 
• Evaluate AI-assisted behaviors beyond correctness, including reliability, failure modes, and operational 
• Automation & AI-Assisted Engineering 
• Build automation for database provisioning, maintenance, monitoring, and remediation. 
• Use AI agents or agent-assisted tooling to support diagnostics, optimization, and operational workflows.

• Integrate databases with AI systems, APIs, and agent frameworks, including MCP- based or equivalent

• Evaluate AI-assisted behaviors beyond correctness, including reliability, failure modes, and operational risk. 
• Ensure database and AI-assisted workflows are observable, traceable, and safe to operate in production. 
• Lead root cause analysis and drive durable remediation after incidents. 
Delivery & Collaboration 
• Partner with application engineering, product, and infrastructure teams to support 
releases, schema changes, and data design. 
• Contribute to SOPs, runbooks, documentation, and operationalstandards. 
• Participate in on-call rotation and production support. 
Technical Leadership 
• Act as a senior technical resource within the database function. 
• Mentor peersthrough design reviews, operational guidance, and knowledge sharing.

Required Qualifications: 

• Bachelor’s degree in computer science, Information Systems, or equivalent practical 
experience. 
• 7+ years of experience in database engineering or administration in complex 
production environments. 
Required Technical Skills 
• Expertise in at least one major RDBMS (SQL Server, Oracle, or PostgreSQL) and 
familiarity with NoSQL (e.g., MongoDB). 
• Strong knowledge of high availability, backup/restore, and disaster recovery strategies. 
• Proven experience in performance tuning and capacity planning. 
• Hands-on experience with cloud database services (AWS, Azure, or GCP) and migration 
projects. 
• Proficiency in scripting and automation (PowerShell, Python) and Infrastructure-as-Code 
tools. 
• Infrastructure-as-Code & automation: Terraform/CloudFormation/Bicep, Ansible, 
CI/CD for database changes (migration scripts, versioning, approvals). 
• Understanding of security and compliance standards (SOC 2, GDPR) for database 
operations. 
• Practical experience with AI-assisted workflows & AI/agent tooling for diagnostics, 
optimization, and automation; ability to evaluate safety, reliability, and failure modes.

• Integration & APIs: safe database integration with AI systems/agents (e.g., MCP- 
based frameworks), REST/GraphQL, job schedulers, and messaging systems