Expert AI: Expert Full Stack Developer: FTC Position: Pretoria Design, development and operations of transactional assets and mainly non-analytics

Introduction

Expert AI: Expert Full Stack Developer:  FTC Position: Pretoria

Design, development and operations of transactional assets and mainly non-analytics

Duties & Responsibilities

Must Have:  AI Engineering

• AI / Machine Learning certification

• AI-assisted implementation and refactoring.

• AI-assisted test generation and quality engineering.

• AI-supported code review and documentation.

• Ability to build reusable AI-enabled developer tooling and workflows.

• Strong understanding that AI-generated outputs still require accountable engineering review.

• Expert knowledge of LLMs and Generative AI application engineering.

• Hands-on experience building production-grade LLM applications and AI agents.

• AI guardrails and human approval mechanisms.

• AI observability, reliability and production monitoring.

• Responsible and secure AI engineering.

• The source role already identifies agents, RAG, prompt/context engineering, tool integration, evaluation, guardrails and human approval gates as core AI engineering capabilities.

• Strong practical capability using AI throughout the software engineering lifecycle.

• AI Native Engineering

• The reference specification explicitly expects responsible AI-assisted development across specification,  coding, review, testing, documentation and operations while retaining accountability for correctness and security.

• Design and implementation of data models suitable for AI and application consumption.

• Integration between Snowflake, AI services, APIs and enterprise applications.

• Success is not measured by the number of AI proofs-of-concept created. The Expert AI Engineer will establish

Desired Experience & Qualification

Experience should include

• Strong understanding of Retrieval-Augmented Generation (RAG).

• Prompt and context engineering.

• Agent/tool integration and orchestration.

• Structured outputs and tool calling.

• Model and application evaluation.

• Specification-driven development.

• Software & Platform Engineering

• Expert Python engineering.

• Strong API and microservice engineering.

• REST-based service integration.

• Event-driven and asynchronous architecture.

• Containers and Kubernetes.

• CI/CD and automated testing.

• Infrastructure as Code.

• Secure software development.

• Production observability and operational readiness.

• Strong architecture and systems-thinking capability.

• Python/Java, APIs, microservices, AWS/cloud-native engineering, Docker/Kubernetes/Terraform, automated testing, CI/CD and production readiness are all represented in the reference Expert specification.

• Snowflake & Data Engineering

• Strong Snowflake engineering and implementation capability.

• Advanced SQL.

• Data ingestion and transformation.

• ETL/ELT engineering.

• Metadata, lineage and data quality.

• Secure data access patterns.

• Performance and cost-conscious data engineering.

Interested?

What Success Looks like

• Reusable, secure and production-ready AI and Snowflake capabilities that enable DVF teams to move AI use cases from idea to production faster, while embedding AI Native engineering practices into the way DVF builds and operates software

To Apply

Please apply with an updated CV

jino@aridconsulting.co.za