Senior Full Stack AI Platform Engineer (Backend focus) - PT - Worldwide

Primary Objective

Client is an advanced enterprise SaaS platform for strategy execution, decision intelligence, governance, and AI driven analysis.

The platform is already substantially built and deployed. We are looking for 1 highly experienced senior engineer to help close the current development phase, harden the platform for enterprise customers, complete security and production readiness work, and support the transition into active sales.

This is not a role to rebuild the product from scratch. The focus is to understand the existing architecture, preserve approved business logic, complete remaining production work, improve reliability and security, and prepare the platform for enterprise customer deployment.

Required Technical Experience

Frontend (Lower priority)

• Strong React experience
• Strong TypeScript and JavaScript experience
• Experience working with large existing applications
• State management and complex application workflows
• Enterprise dashboards and data intensive interfaces
• Ability to improve existing architecture without unnecessary rewrites

Backend

• Advanced Node.js experience
• REST API design and implementation
• Authentication and authorization middleware
• Validation and error handling
• Production API debugging
• Integration architecture

AWS
Strong hands on AWS production experience, including:
AWS Lambda, AWS Amplify, API Gateway, AWS Cognito, AWS RDS, PostgreSQL, S3, CloudWatch, IAM, Secrets managementm Backup and recovery, Security configuration, CI/CD

• Experience with serverless SaaS architecture is strongly preferred.

Database and Multi Tenant SaaS
Strong PostgreSQL experience, Row Level Security, Multi tenant isolation, Workspace and organization scoped data, Schema migrations, Indexes and query optimization, Transactions, Referential integrity, Soft delete architecture, Audit trails, Least privilege database access, Data integrity and recovery

AI, LLMs, and Agents, Critical Requirement
This role requires strong practical experience building production AI systems. Candidates should have substantial experience with:
LLM APIs and production integrations, AI agents, Tool calling, Agent orchestration, Multi step AI workflows, Agent state and memory, Structured outputs, JSON schemas, Prompt architecture, Prompt versioning, Context engineering, RAG, Retrieval and grounding, AI evaluation systems, Regression testing for AI behavior, Model selection and routing, Retries and fallback strategies, Hallucination control, Human review workflows, AI provenance and explainability, Token and cost management, Latency optimization, AI observability and tracing, Prompt injection protection, AI data leakage prevention, Secure handling of tenant specific context

The candidate must understand the difference between probabilistic AI behavior and deterministic software logic.

The company uses AI extensively, but core formulas, governance rules, permissions, quantitative calculations, audit logic, and authoritative business rules must remain deterministic and controlled by software.
Experience simply connecting an OpenAI API to a chatbot is not sufficient.

Enterprise Security
Strong understanding of:
OWASP application security, Authentication and authorization, IAM and least privilege, Tenant isolation testing, API security, SQL injection prevention, Cross site scripting prevention, Security headers, Rate limiting, Secrets management, Encryption, Audit logging, Vulnerability remediation, Dependency security, Secure file handling, Security monitoring, Penetration test remediation, SOC 2 technical readiness

The engineer does not need to be a SOC 2 auditor, but must be capable of implementing and documenting technical controls required for SOC 2 readiness and enterprise security reviews.

What You Will Be Responsible For

• Review and understand the existing architecture before making changes.
• Complete remaining approved functionality required for commercial release.
• Harden the platform for enterprise production use.
• Validate frontend, backend, database, authentication, and AWS integration end to end.
• Ensure reliable persistence and data integrity across the platform.
• Verify multi tenant isolation and workspace security.
• Improve application reliability, logging, monitoring, observability, and error handling.
• Identify and remediate production risks.
• Prepare the technical environment for penetration testing and SOC 2 readiness.
• Remediate findings from external security testing.
• Strengthen our AI and agent architecture.
• Improve reliability of AI workflows and structured outputs.
• Help establish AI evaluation and regression testing.
• Support technical customer onboarding and enterprise integrations.
• Assist with enterprise security questionnaires and technical architecture discussions when needed.
• Support production issues after customer deployment.

Important Engineering Expectations

• Preserve existing validated business logic.
• Do not rewrite working systems simply because another architecture is preferred.
• Investigate before modifying.
• Understand the cause of a problem before implementing a fix.
• Work safely within defined scope.
• Respect locked formulas, governance logic, schemas, and approved architecture.
• Maintain deterministic behavior wherever business rules require it.
• Build for security, reliability, auditability, and enterprise scale.
• Document important architectural and implementation decisions.

Ideal Background

• Approximately 8 to 15 years of professional software engineering experience is preferred, although demonstrated capability is more important than years.
• Experience taking a multi tenant SaaS product into production.
• Experience supporting real enterprise customers.
• Strong full stack background.
• Strong AWS architecture background.
• Strong AI and LLM engineering experience.
• Experience with security hardening.
• Experience with SOC 2 environments is highly desirable.
• Experience working with founder led products or complex existing codebases is valuable.

You do not need to be the world's best specialist in every area, but you must be senior enough to understand the entire platform and take technical ownership across the stack.

This Role Is Probably Not a Fit If

• Your experience is primarily frontend development.
• You have limited production AWS experience.
• You have never worked on multi tenant enterprise SaaS.
• Your AI experience is limited to basic chatbot integrations.
• You prefer rebuilding existing applications rather than understanding them.
• You require detailed day to day technical supervision.
• You have not supported production systems used by real customers.

Success in This Role

Success means we reaches a state where we can confidently sell it to enterprise customers knowing that the platform is stable, secure, observable, recoverable, technically defensible, and ready to pass serious customer IT and security scrutiny.