Artificial Intelligence Engineer

About ShaqoAI

ShaqoAI operates an AI workforce platform enabling businesses to automate operations and coordinate intelligent AI agents across multiple domains such as sales, customer support, finance, administration, and general operations. The platform emphasizes autonomous execution combined with human oversight, where routine operational tasks are handled by AI agents, and humans focus on critical, strategic decisions. ShaqoAI integrates with existing business systems to transform fragmented processes into cohesive, intelligent workflows, envisioning a future where AI manages repetitive work while humans concentrate on strategy, creativity, and relationships.

Role Overview

We are seeking an Artificial Intelligence Engineer to design, build, assess, and deploy the AI technology that powers our digital workforce. This role combines expertise in Generative AI, Large Language Models (LLMs), AI agents, machine learning, NLP, software development, and automation. Key responsibilities include developing AI agents capable of understanding business contexts, reasoning through tasks, interacting with external tools, retrieving information, making decisions within set boundaries, and reliably executing workflows, all while maintaining human control.

Key Responsibilities

• Design and implement intelligent AI agents for various business processes.
• Create agentic systems that support planning, reasoning, tool usage, and task execution.
• Integrate LLMs from providers like OpenAI, Anthropic, Google, or open-source alternatives.
• Develop structured prompting, function/tool invocation, and agent workflows.
• Build Retrieval-Augmented Generation (RAG) systems and knowledge retrieval pipelines.
• Develop systems managing context, memory, task planning, and multistep execution.
• Ensure AI systems include proper human oversight and approval mechanisms.
• Develop and evaluate machine learning and NLP applications including text classification, information extraction, semantic search, embeddings, entity recognition, and conversational AI.
• Fine-tune or adapt models to specific use cases.
• Experiment with emerging AI architectures, models, frameworks, and techniques.
• Create data pipelines for training, evaluation, and inference.
• Develop automated evaluation frameworks to measure AI agents' accuracy, latency, cost efficiency, reliability, and task completion.
• Identify and mitigate failure modes such as hallucinations, incorrect tool use, and prompt injections.
• Implement guardrails and validation for high-impact workflows.
• Enhance agent performance through iterative feedback and evaluation.
• Integrate AI services into production APIs and applications, ensuring scalable deployment in cloud and distributed environments.
• Optimize model inference for performance and cost.
• Monitor AI systems, troubleshoot failures, and maintain high-quality production code.
• Participate actively in architectural decisions, documentation, code reviews, and maintain engineering standards.
• Collaborate closely with engineers, product managers, designers, and business teams to translate requirements into AI solutions and communicate complex concepts effectively.
• Stay current with advancements in LLMs, agentic AI, machine learning, and AI infrastructure.

Qualifications and Skills

Applicants should possess a strong technical background in Computer Science, Software Engineering, Machine Learning or closely related field along with proficiency in Python programming. Practical experience with AI or machine learning applications is required, including familiarity with LLMs, generative AI, prompt engineering, embeddings, vector search, RAG systems, and function calling. Experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, and knowledge of NLP and modern language model architectures is essential. Candidates should be comfortable integrating AI models via APIs and have a solid foundation in software engineering practices such as Git version control, testing, and debugging. Strong analytical, problem-solving, and collaborative skills are necessary.

Preferred candidates will have experience in building AI agents or agentic workflows utilizing frameworks like LangChain, LangGraph, LlamaIndex; working with vector databases such as Pinecone, Weaviate, or Qdrant; cloud platforms (AWS, Azure, Google Cloud); containerization with Docker; distributed systems; AI evaluation platforms; and implementing AI security and guardrails. Knowledge of multimodal AI and developing AI solutions for business automation or enterprise workflows is an added advantage. Contributions to open source, research publications, or a robust GitHub portfolio are highly valued.

Education & Experience

A Bachelor's degree or higher in Computer Science, AI, Mathematics, Engineering or related fields is preferred, though candidates with equivalent practical experience are welcome. Proven competence demonstrated through personal projects, open-source contributions, research, internships, freelance work, or professional engagements is highly encouraged.

Potential Projects

• AI agents supporting customer service
• Automated sales agents
• Finance and administration AI solutions
• Document understanding and processing systems
• Intelligent communication agent development
• Enterprise knowledge assistant platforms
• RAG and semantic search deployments
• Automated AI-powered workflow systems
• Multi-agent AI ecosystems
• AI decision support and human-in-the-loop approvals
• Agent evaluation and monitoring frameworks

Employment Details and Compensation

This is a full-time remote role based in Nairobi County, Kenya, offering a monthly salary range of 30000 to 50000 Kenyan Shillings dependent on experience and demonstrated technical expertise. The compensation is competitive and aligned with performance-based career growth. The hiring process incorporates multiple stages including CV and portfolio review, initial conversation, technical assessments, and interviews with engineering leaders.

Privacy and Equal Opportunity

Applicant information is treated confidentially and is used solely for recruitment purposes. The company is committed to diversity and inclusion, equal opportunity in hiring based on merit, skill, potential, and business needs, encouraging candidates from varied backgrounds to apply.