Senior AI Engineer

I Grow Wealth Investments; Durbanville; On-site; ZAR 900,000 - 1,300,000; Full time

Job summary

I Grow Wealth Investments in Durbanville, Western Cape, seeks an experienced backend/AI engineer to build production AI applications using Node.js and TypeScript. You will design APIs, event-driven systems, and agentic workflows that leverage multiple LLM providers and tool calls to solve real business tasks.

You will work with PostgreSQL, embeddings and vector search, plus graph databases, to architect scalable data models and memory systems.

Qualifications

• Advanced Node.js experience is strongly preferred.
• Advanced TypeScript experience is required.
• Strong backend software engineering and API design skills.
• Strong PostgreSQL knowledge and relational data modelling expertise.
• Solid understanding of database performance and query tuning.
• Practical understanding of LLMs and modern AI application development.
• Experience with vector databases / pgvector and embeddings.
• Understanding of graph databases and knowledge graphs.
• Experience with agentic AI, tool calling and multi-step AI workflows.

Responsibilities

• Build production AI applications and agentic systems using Node.js and TypeScript.
• Design backend services, APIs, integrations and event-driven systems.
• Create agentic workflows where AI agents use tools, data and other agents to complete real tasks.
• Work with LLMs from multiple providers, managing context and tool calling.
• Design AI memory and organisational knowledge systems.
• Work with PostgreSQL extensively, including schema design and complex queries.
• Implement embeddings, semantic search and vector retrieval (pgvector / vector databases).
• Engage with graph data and relationships across people, systems, and processes.
• Build integrations with internal and external systems via APIs.
• Develop reliable long-running AI processes with scheduled events and async execution.
• Promote engineering patterns, reusable components and quality standards for AI-first development.

Tools

Node.js

TypeScript

Backend design

API design

PostgreSQL

Relational data modelling

LLMs & AI apps

Embeddings

Vector search

pgvector

Graph databases

Agentic AI

API integrations

AWS

Docker

OAuth/OIDC

Event-driven architectures

Version control (Git)

Job description

Minimum requirements (Advantageous):

• Advanced commercial Node.js experience.
• Advanced TypeScript.
• Strong backend software engineering and API design.
• Strong PostgreSQL knowledge.
• Solid understanding of relational data modelling and database performance.
• Practical understanding of LLMs and modern AI application development.
• Understanding of embeddings, semantic similarity and vector search.
• Experience with or strong understanding of vector databases / pgvector.
• Understanding of graph databases and knowledge graphs.
• Understanding of agentic AI, tool calling and multi-step AI workflows.
• Experience building integrations between different systems and APIs.
• Comfortable with asynchronous processing, queues, scheduled jobs and event-driven architectures.
• Strong Git and modern software-development practices.
• Experience using AI coding agents/coding assistants as part of serious software development, not simply autocomplete.
• AWS, Docker, ECS, S3, Redis, Bedrock, OpenAI, Anthropic, Mastra, MCP, RAG architectures, pgvector, Neo4j or other graph databases.
• OAuth/OIDC, event-driven architectures, workflow engines and infrastructure as code.

Duties and responsibilities include, but not limited to:

• Build production AI applications and agentic systems using Node.js and TypeScript.
• Design backend services, APIs, integrations and event-driven systems.
• Build agentic workflows where AI agents use tools, data and other agents to complete real business tasks.
• Work with LLMs from multiple providers and understand model selection, context management and tool/function calling.
• Design and implement AI memory and organisational knowledge systems.
• Work extensively with PostgreSQL, including schema design, complex queries, performance and production data architecture.
• Implement embeddings, semantic search, RAG and vector retrieval, including PostgreSQL/pgvector and dedicated vector databases where appropriate.
• Understand and work with graph data and graph databases, including relationships between people, systems, processes, documents and organisational knowledge.
• Build integrations with internal and external systems through APIs, MCP servers and other tool interfaces.
• Design reliable long-running AI processes involving scheduled events, human approvals and asynchronous execution.
• Use modern AI coding agents as a core part of the development process while maintaining engineering quality, testing and code review.
• Help establish engineering patterns, reusable components and technical standards for AI-first development.