Senior Full-Stack Software Engineer - Platform And AI Systems

Senior Full-Stack Software Engineer - Platform & AI Systems 

About SUPERWISE Chat 

SUPERWISE Chat is an enterprise, multi-tenant generative AI platform combining conversational AI, governance, persistent memory, knowledge management, enterprise data connectivity, and policy enforcement. 

The platform spans TypeScript/Node.js, Next.js/React, PostgreSQL with pgvector, Redis, asynchronous workflows, and containerized cloud infrastructure. At its center is the Cognitive Control Layer (CCL), a multi-stage orchestration pipeline for intent, context, retrieval, policy and guardrail enforcement, LLM interaction, memory, and post-turn workflows. 

This is a production enterprise system. Security boundaries, tenant isolation, reliability, observability, auditability, and failure behavior matter as much as feature functionality. 

The Role 

We are looking for a Senior Full-Stack Software Engineer with particular depth in backend, platform, data, and distributed-system engineering. 

You will own production capabilities end to end, from architecture and data design through APIs, asynchronous processing, frontend integration, testing, deployment, and operational support. 

We use agentic development workflows to increase the scope, speed, and quality an experienced engineer can deliver. Your engineering experience is the control layer over that process. You should be comfortable directing AI coding agents through substantial implementation work while independently evaluating architecture, data models, security assumptions, failure behavior, and production readiness. 

The successful candidate combines deep engineering judgment with genuine curiosity about how generative AI changes the way software should be engineered. 

What You Will Own 

• Design and implement production services using TypeScript, Node.js, and Express or comparable server-side frameworks. 

• Own REST APIs, service boundaries, validation, error handling, rate limiting, and observability. 

• Design PostgreSQL schemas, migrations, indexes, transactions, and query patterns for complex enterprise workloads. 

• Build asynchronous and event-driven workflows using Inngest, Redis, queues, and background workers. 

• Design for concurrency, partial failure, retries, timeouts, idempotency, and changing workload volumes. 

• Build and maintain strict tenant isolation across application, data, retrieval, cache, and asynchronous execution paths. 

• Implement and evolve PostgreSQL Row-Level Security and associated behavioral testing. 

• Work with OIDC/JWT identity, authentication, RBAC, resource-level permissions, and delegated access patterns. 

• Extend the SUPERWISE CCL and integrate LLM providers, tools, retrieval, memory, policy enforcement, guardrails, and post-processing. 

• Build systems in which agents can invoke tools and enterprise data without bypassing identity, authorization, governance, or audit controls. 

• Build document, web, database, and cloud-storage connectors and retrieval pipelines using PostgreSQL, pgvector, and embeddings. 

• Independently extend React and Next.js interfaces needed to complete vertical product slices. 

• Diagnose production issues across application, database, integration, infrastructure, and external-service boundaries. 

Agentic Engineering Is Part of the Job 

• Use modern agentic coding systems as part of your normal engineering workflow, not merely for autocomplete or experimentation. 

• Use structured specifications and clear acceptance criteria to direct substantial agentic implementation. 

• Decompose larger capabilities into coherent workstreams that can execute independently or in parallel. 

• Provide agents with appropriate context, constraints, architecture, and quality expectations before implementation. 

• Review generated architecture and code using your own engineering judgment rather than accepting output because it functions. 

• Recognize when an agent has produced something locally correct but systemically wrong. 

• Understand agent-produced implementation well enough to explain, operate, debug, modify, and defend it. 

• Use automated tests, static analysis, code review, architectural constraints, and runtime evidence to validate agent-produced work. 

• Know when direct human engineering is faster or safer than further prompting. 

• Continuously adapt your engineering process as agentic development capabilities evolve. 

Required Experience 

• 7+ years of professional software engineering experience. 

• Strong production backend engineering experience with TypeScript and Node.js, or deep adjacent backend experience with demonstrated current TypeScript proficiency. 

• Strong PostgreSQL experience including schema design, migrations, transactions, indexing, query optimization, and production troubleshooting. 

• Experience building and operating APIs and distributed application services. 

• Experience with multi-tenant SaaS, authorization, security boundaries, or systems where data isolation materially matters. 

• Experience with Redis, asynchronous processing, queues, workers, or comparable distributed workflow mechanisms. 

• Working proficiency with React and modern frontend development sufficient to independently deliver end-to-end capabilities. 

• Experience with automated testing, CI/CD quality gates, code review, and production debugging. 

• Demonstrated use of AI-assisted or agentic coding systems in substantive software-development work. 

• Ability to explain the architecture and mechanisms of systems you have built regardless of how much implementation was produced through AI. 

Preferred Experience 

• PostgreSQL Row-Level Security and pgvector or other vector retrieval systems. 

• RAG and enterprise knowledge-retrieval architectures. 

• LLM tool use, agent orchestration, guardrails, policy enforcement, AI governance, or human-in-the-loop systems. 

• OIDC, OAuth, JWT, enterprise SSO, RBAC, or ABAC. 

• OpenTelemetry and structured production observability. 

• Python/FastAPI, GitLab CI, GCP, Docker, and containerized production environments. 

• Enterprise integrations involving external APIs, SQL data sources, document systems, or cloud storage. 

• Experience with security, compliance, governance, or audit requirements. 

Technology Environment 

• Backend: Node.js 22+, TypeScript, Express, Zod, Pino, Python/FastAPI. 

• Frontend: Next.js 15, React 19, Tailwind CSS 4, Radix UI. 

• Data: PostgreSQL 16, pgvector, Redis 7. 

• AI and Platform: CCL orchestration, LLM providers, embeddings, retrieval, tools, guardrails, policy enforcement, persistent memory. 

• Authentication and Authorization: OIDC, JWT, Frontegg, RBAC, PostgreSQL RLS. 

• Workflows and Integrations: Inngest, Socket.io, SSE, Stripe, GCP, enterprise data connectors. 

• Testing and Infrastructure: Vitest, Testing Library, Playwright, Docker Compose, GitLab CI, OpenTelemetry. 

• Exact prior experience with every technology is not required. We value transferable engineering depth and demonstrated ability to become productive quickly in adjacent technologies. 

What Strong Performance Looks Like 

• Independently own significant production capabilities rather than waiting for detailed implementation instructions. 

• Increase delivery velocity through agentic engineering without reducing quality, security, maintainability, or understanding. 

• Identify architectural problems before they become production incidents. 

• Explain why a system works, where it will fail, and what evidence shows it is operating correctly. 

• Preserve tenant and authorization boundaries across synchronous, asynchronous, retrieval, and agentic execution paths. 

• Hold human-written and agent-produced code to the same production standards. 

• Reduce the amount of senior oversight required to move a capability safely from intent to production. 

What We Value 

• Engineering judgment: understand why systems work, not merely how to make them work. 

• Ownership: carry capabilities through production and understand their operational behavior. 

• Agentic leverage: use AI to multiply strong engineering rather than substitute for engineering knowledge. 

• Security thinking: treat identity, authorization, tenant boundaries, and data protection as architecture. 

• Curiosity: hold strong engineering priors without becoming rigid about methods. 

• Candor: say what you know, what you do not know, and what evidence you need. 

• Adaptability: move between architecture, database design, backend implementation, frontend integration, testing, and production diagnosis. 

SUPERWISE is an equal opportunity employer, dedicated to fostering a diverse and inclusive workplace. We welcome applications from all qualified individuals, irrespective of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Join us in our commitment to excellence and innovation and take the next step in your career with us.