Artificial Intelligence Engineer

Artificial Intelligence EngineerShaqoAI • Full-time • Nairobi County, Kenya • RemoteAbout ShaqoAIShaqoAI is an AI workforce platform that helps businesses automate operations and coordinate intelligent AI agents across sales, customer support, finance, administration, and operations.Our platform is built around autonomous execution with human control. AI agents handle routine and repetitive operational tasks while humans remain involved in sensitive, high-impact, or strategic decisions.ShaqoAI connects with existing business tools and systems to transform fragmented processes into intelligent, connected workflows. Our vision is to build the future of work—where people focus on strategy, creativity, relationships, and decision-making while AI handles repetitive operational workloads.Our mission is to give every business access to a capable digital workforce that enables them to work smarter, automate more, and scale further.About the RoleWe are looking for an Artificial Intelligence Engineer to help design, build, evaluate, and deploy the AI systems powering ShaqoAI's digital workforce.You will work at the intersection of Generative AI, Large Language Models (LLMs), AI agents, machine learning, NLP, software engineering, and automation.You will help build AI agents capable of understanding business context, reasoning through tasks, interacting with external tools, retrieving relevant information, making decisions within defined boundaries, and executing workflows reliably.This is a highly hands-on engineering role. You will work closely with software engineers, product teams, and business stakeholders to turn AI capabilities into reliable production systems.Key ResponsibilitiesAI & Agent EngineeringDesign and develop intelligent AI agents for business workflows.Build agentic systems capable of planning, reasoning, tool use, and task execution.Integrate and orchestrate LLMs from providers such as OpenAI, Anthropic, Google, or open-source models.Develop structured prompting, function/tool calling, and agent workflows.Implement Retrieval-Augmented Generation (RAG) systems and knowledge retrieval pipelines.Develop systems for context management, memory, task planning, and multi-step execution.Build AI systems that maintain appropriate human oversight and approval mechanisms.Machine Learning & NLPDevelop and evaluate machine learning and NLP solutions.Work with text classification, information extraction, semantic search, embeddings, entity recognition, and conversational AI.Fine-tune or adapt models where appropriate.Experiment with emerging AI architectures, models, frameworks, and techniques.Build data pipelines for training, evaluation, and inference.AI Evaluation & ReliabilityDevelop automated evaluation frameworks for AI agents and LLM-based systems.Measure accuracy, latency, cost, reliability, and task-completion performance.Identify and reduce hallucinations, incorrect tool usage, prompt injection, and other failure modes.Design guardrails and validation mechanisms for high-impact workflows.Continuously improve agent performance using real-world feedback and evaluation data.Production EngineeringIntegrate AI services into production APIs and applications.Deploy and operate AI systems in cloud and distributed environments.Optimize model inference, latency, scalability, and infrastructure costs.Monitor AI systems and investigate production failures.Write clean, maintainable, well-tested production code.Contribute to technical architecture, documentation, code reviews, and engineering standards.CollaborationWork closely with software engineers, product managers, designers, and business teams.Translate business requirements into practical AI solutions.Explain complex AI concepts clearly to technical and non-technical stakeholders.Stay current with developments in LLMs, agentic AI, machine learning, and AI infrastructure.Required QualificationsStrong foundation in Computer Science, Software Engineering, Machine Learning, or a related technical discipline.Strong programming skills in Python.Practical experience building AI or machine learning applications.Experience working with LLMs and Generative AI systems.Understanding of prompt engineering, embeddings, vector search, RAG, and tool/function calling.Experience with machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies.Understanding of NLP concepts and modern language-model architectures.Experience working with APIs and integrating AI models into software applications.Understanding of software engineering fundamentals, including Git, testing, debugging, APIs, and version control.Ability to work with data, evaluate model performance, and conduct structured experiments.Strong analytical and problem-solving skills.Ability to work effectively in a collaborative engineering environment.Preferred QualificationsExperience building AI agents or agentic workflows.Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar technologies.Experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, or pgvector.Experience with cloud platforms such as AWS, Azure, or Google Cloud.Experience with Docker and containerized deployments.Experience with distributed systems, microservices, or event-driven architectures.Experience with AI observability and evaluation platforms.Experience implementing AI security, guardrails, access controls, or responsible AI practices.Experience with multimodal AI is an advantage.Experience building AI solutions for business automation or enterprise workflows is highly desirable.Contributions to open-source projects, published research, technical projects, or a strong GitHub portfolio are highly valued.Education & ExperienceA Bachelor's degree or higher in Computer Science, Software Engineering, Artificial Intelligence, Mathematics, Engineering, or a related field is preferred.However, equivalent practical experience will be considered.We care more about what you can build than the title of your degree.Candidates who can demonstrate strong AI engineering ability through projects, open-source contributions, research, internships, freelance work, or professional experience are encouraged to apply.What You'll BuildAs part of the ShaqoAI engineering team, you may work on systems such as:AI agents for customer supportSales automation agentsFinance and administrative agentsDocument understanding and processingIntelligent email and communication agentsEnterprise knowledge assistantsRAG and semantic search systemsAI-powered workflow automationMulti-agent systemsAI decision-support systemsAgent evaluation and monitoring infrastructureHuman-in-the-loop approval systemsWhat We OfferCompetitive salary based on experience and technical capability.Performance-based growth opportunities.Opportunity to work directly on production-grade AI systems.Hands-on experience with modern LLM and agentic AI technologies.Collaborative engineering environment.Professional development and learning opportunities.Opportunity to contribute to the architecture and direction of an emerging AI technology company.Exposure to real-world AI automation across multiple business domains.Potential opportunities for increased responsibility as ShaqoAI scales.Salary: KES 30-50k per month, depending on experience and demonstrated technical ability.Working ArrangementLocation: Nairobi County, KenyaWork arrangement: On-siteEmployment type: Full-timeHiring ProcessOur hiring process is designed to evaluate both technical ability and practical problem-solving.Application Review — We review your CV, portfolio, GitHub, projects, and relevant experience.Initial Interview — A conversation about your experience, interests, and approach to AI engineering.Technical Assessment — A practical AI engineering challenge focused on solving a real-world problem.Technical Interview — Discussion of your solution, AI architecture, engineering decisions, and technical fundamentals.Team/Final Interview — Discussion with the engineering and leadership team.Offer — Successful candidates receive an employment offer and onboarding information.We encourage candidates to demonstrate their ability through real projects, GitHub repositories, technical portfolios, research, or practical AI applications.Applicant PrivacyShaqoAI will use applicant information solely for recruitment and employment-related purposes.Application information will be handled confidentially and accessed only by authorized personnel involved in the hiring process. Candidate information will not be sold or used for unrelated commercial purposes.By applying, candidates consent to ShaqoAI processing their submitted information for the purposes of evaluating their application and managing the recruitment process.Equal OpportunityShaqoAI is committed to building a diverse and inclusive team. Employment decisions are based on qualifications, skills, experience, potential, and business requirements.We encourage applications from talented individuals with diverse backgrounds and perspectives.How to ApplySubmit your CV/resume and relevant portfolio or GitHub profile through www.linkedin.com/in/jakesmurilaIf you have built an AI agent, LLM application, RAG system, machine learning project, automation platform, or other relevant technology, show us what you built.We are looking for engineers who don't just understand AI, they build with it.