Senior AI Developer

2 weeks ago


Cape Town, Western Cape, South Africa Plan CreativeNest South Africa Full time R800 000 - R1 200 000 per year

We are looking for a highly skilled and experienced Senior AI Developer to join our AI & Automation team. In this role, you will design and implement cutting-edge AI solutions with a strong focus on autonomous agents, machine learning workflows, and cloud-native architectures to drive innovation in the marketing industry.

Our team develops intelligent, scalable systems that power automation and optimization across marketing channels — from content generation and personalization to campaign performance analysis and predictive insights. You will work at the intersection of AI, marketing technology, and software engineering, building serverless solutions on AWS that enable measurable business impact.

This is a hands-on technical role that requires deep expertise in AI system development as well as practical experience with AWS services and modern backend architectures. You'll be part of a distributed, cross-functional team shaping how AI transforms marketing.

Responsibilities

  • Design, develop, and deploy AI-driven systems and agent-based architectures on AWS
  • Build intelligent workflows using AWS serverless services (e.g. Lambda, Step Functions, DynamoDB, S3, EventBridge)
  • Integrate language models (Amazon Bedrock) into scalable applications
  • Develop and orchestrate autonomous agents for data processing, decision-making, or task automation
  • Design and optimize prompts to maximize the performance of LLM-based systems
  • Fine-tune foundational models and apply NLP techniques to align AI behavior with business needs
  • Collaborate with data scientists, backend engineers, and DevOps to bring AI models into production
  • Implement monitoring, logging, and error handling to ensure system reliability and performance
  • Design and integrate data ingestion and preprocessing workflows for structured and unstructured data
  • Ensure compliance with data protection policies and implement secure-by-design principles when handling confidential marketing data
  • Contribute to architecture and infrastructure decisions for AI services
  • Apply a "cloud-native" and "infrastructure-as-code first" mindset when designing and deploying solutions
  • Design systems with a clear understanding of stateful vs. stateless architectures and their impact on scalability, reliability, and cost

Requirements

  • 5+ years of experience in software development, including at least 2 years working specifically with AI or machine learning systems
  • Strong experience with AWS services such as Lambda, API Gateway, Step Functions, DynamoDB, S3, EventBridge, CloudWatch, IAM, Amazon Bedrock, and SSM Parameter Store
  • Hands-on experience with prompt engineering and designing effective interactions with large language models (LLMs)
  • Experience fine-tuning foundation models and applying natural language processing (NLP) techniques
  • Proven track record in building agent-based architectures or intelligent automation systems
  • Proficient in Python with a strong grasp of software engineering best practices
  • Solid experience with Git and GitHub workflows for collaborative software development
  • Deep understanding of event-driven and serverless architectures, and the ability to assess trade-offs with container-based approaches
  • Familiarity with MLOps concepts and tools for model deployment, monitoring, and versioning
  • Experience using infrastructure-as-code tools such as Terraform or AWS CloudFormation
  • Understanding of the full software development lifecycle (SDLC), from planning and design to deployment and maintenance
  • Strong problem-solving skills and the ability to work independently in an agile, fast-paced environment
  • Excellent communication and collaboration skills across technical and non-technical teams

Nice to Have

  • Experience with vector databases such as Pinecone, FAISS, Weaviate, ChromaDB, or Milvus
  • Knowledge of agent frameworks like LangChain, CrewAI, AutoGen, or LangGraph
  • Experience with real-time data processing tools such as Kinesis or Kafka
  • Familiarity with machine learning frameworks such as TensorFlow or PyTorch
  • Relevant AWS certifications (e.g., AWS Certified AI Practitioner)

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