• Work closely with Product Managers/Senior Leadership to frame problems within the business context and deliver the highest impact to our users • Design, implement and ship new features with a high level of responsibility and OWNERSHIP • Implement scalable solutions to consistently serve a vast global user base • Help establish architecture based on technology and our needs • Build, train, and test Machine learning/AI solutions focusing on natural language processing, recommender systems, computer vision • Write well-crafted, well-tested, maintainable code to convert our ML models into working pipelines • Collaborate closely with Frontend, DevOps, and Data Engineering teams to deliver cohesive end-to-end solutions, align on technical decisions, and ensure smooth integration between system components • Participate in code-reviews to ensure code quality and distribute knowledge • Monitor and troubleshoot existing features and resolve any issues that arise

• FlexiSAF is a leading EdTech company driving innovation in education across Africa. • Launching a specialized AI Engineering Training and Internship Program designed to equip passionate software developers with the skills and hands-on experience needed to transition into full-fledged AI Engineers. • Over four intensive months, participants will learn to design and build intelligent, LLM-powered applications using modern frameworks such as LangChain, Retrieval-Augmented Generation (RAG) and vector databases. • Emphasis on practical, project-based learning; from implementing AI-driven workflows and chatbots to integrating models into production-ready applications. • Trainees will also gain exposure to Spring Boot for enterprise API integration and containerization for scalable deployments. • Ideal candidates are curious, driven individuals with a strong foundation in programming who are eager to explore the fast-evolving world of Generative AI. • Upon successful completion, participants will be well-positioned to take on AI Engineering roles within any organization building intelligent products and systems.

• Architect and maintain the LLMOps/GenAIOps toolchain, including model registries, prompt version control, and reproducible training pipelines. • Implement and manage the Azure AI Foundry environment, configuring model routers, quota management, and private endpoints for secure inferencing. • Develop comprehensive observability dashboards to track model latency, token costs, hallucination rates, and drift. • Automate "Policy-as-API" controls within the orchestration layer to enforce governance guardrails (e.g., PII filtering) at runtime. • Collaborate with the Platform SRE team to ensure high availability and disaster recovery for mission-critical clinical agents. • Manage the "Model Registry," ensuring all deployed models have associated version history, performance metrics, and rollback targets. • Configure and maintain "Vector Databases" and RAG pipelines, optimizing retrieval performance and index freshness. • Implement "Prompt Filtering" and content moderation gateways to prevent jailbreaks and enforce safety standards at the infrastructure level. • Develop "Blue/Green" or "Canary" deployment strategies for AI agents to safely test new model versions in production. • Manage the "API Gateway" for all AI services, ensuring authentication, rate limiting, and usage logging are enforced. • Optimize "GPU/CPU Orchestration" to control compute costs while maintaining performance SLAs for high-volume inference. • Build automated "Drift Detection" alerts that trigger retraining or human review when model performance degrades below a set threshold. • Perform any other job related duties as requested.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role is a hands-on, high-impact engineering position focused on building scalable AI and ML systems that drive automation, intelligence, and data-driven insights. You will work closely with technical and business leaders to design, deploy, and optimize AI architectures, models, and applications, including LLMs, vector databases, and intelligent agents. - Collaborate with leadership and the development team to design and deploy scalable AI/ML architectures and solutions. - Develop, train, and maintain AI models, data pipelines, and integrations with APIs, databases, and SaaS platforms. - Experiment with emerging LLMs, embeddings, vector databases, and orchestration frameworks such as LangChain or Semantic Kernel. - Lead hands-on prototyping of LLM-based applications, intelligent agents, and automation workflows. - Establish AI architecture standards, model governance, and contribute to long-term AI strategy. - Design systems for high availability, scalability, and efficient cloud deployment on Azure, AWS, or GCP. - Create technical documentation, architecture diagrams, and deployment playbooks while participating in code reviews and mentoring junior developers. Qualifications - 5+ years of professional software development experience. - 3+ years of hands-on experience building or designing AI/ML systems. - Proficiency in Python, C#, or similar programming languages. - Experience with LLMs, vector databases, embeddings, and prompt orchestration. - Familiarity with AI/ML frameworks (OpenAI, Hugging Face, LangChain, Semantic Kernel) and cloud platforms (Azure AI, AWS SageMaker, GCP Vertex AI). - Ability to develop and integrate data pipelines, APIs, and AI inference services. - Strong analytical, communication, and collaboration skills. - Capacity to balance hands-on development with high-level system design and strategic planning. - Curiosity and proactive engagement with emerging AI tools, frameworks, and trends. - Must reside in and be authorized to work in the USA. Benefits - Competitive compensation with a salary range of $120,000–$150,000 USD annually. - Comprehensive medical, dental, and vision benefits. - Paid vacation and sick days for work-life balance. - Flexible work options and straight day shifts with no weekends. - Career growth and development opportunities, including tuition reimbursement. - Company-provided equipment for remote or in-office work. - Participation in company events and celebrations. - Collaborative and diverse team environment.