AI Solutions Implementation Lead, Kenya

About Lua

Lua is an Agent Operating System creating digital employees that autonomously perform tasks end-to-end by interacting with company data and workflows without replacing existing systems. These AI agents are not mere chatbots but perform actionable work leveraging the company’s own data, workflows, and integrations. Using Lua’s scripting and orchestration, the company supports infrastructure, model orchestration across providers, various communication channels such as WhatsApp, Slack, Email, and more, plus monitoring tools.

Lua serves diverse clients across Africa, the Middle East, and South Asia, including heritage sites, hospitality groups, large retailers, conglomerates, banks, social commerce, and insurers with millions of customers. Together, these clients employ over 64,000 people generating more than $5 billion in annual turnover. Backed by Y Combinator with $5.8 million in funding, Lua aims to enable businesses to become AI-native on their existing systems without disruption.

Role Responsibilities

• Lead client discovery in East Africa through audits, workshops, and technical sessions to map workflows, data, and pain points, identifying valuable AI agent use cases.
• Translate business challenges into detailed technical scopes, user journeys, success criteria, and deployment plans working closely with product and engineering.
• Be actively involved in configuring, testing, and troubleshooting Lua platform implementations including tools, skills, integrations, webhooks, jobs, channels, and client system connections like CRMs, ERPs, databases, and APIs.
• Conduct thorough testing of agent outputs considering accuracy, reliability, edge cases, permissions, and escalation logic; manage pilots, feedback cycles, and deployment approvals.
• Oversee project delivery by managing timelines, dependencies, blockers, risks, and ensuring client collaboration for data, access, and stakeholder engagement.
• Document implementations including process maps, SOPs, test plans, training guides supporting onboarding, adoption, and early monitoring.
• Develop repeatable implementation playbooks, templates, and quality assurance standards for the East Africa region based on learned experiences.

Performance Metrics

Success is gauged by the quality of client audits, clarity in solution design, speed and reliability of deployments, client satisfaction, adoption rates, and converting pilots into scalable implementation models. Within the first 90 days, the lead is expected to handle at least one full implementation cycle from discovery through to pilot or deployment.

Candidate Profile

Essential Qualifications:

• Minimum 7 years in technical implementation, solution engineering, software delivery, or technical consulting with at least 3 years hands-on experience working with software systems, APIs, and integrations.
• Direct experience with AI tools, large language models, agents, retrieval-augmented generation (RAG), or workflow automation in live deployments including strong testing discipline for edge cases, permissions, escalations, and production readiness.
• Proven ability engaging with clients for discovery, workshops, solution design, testing, deployment, and training, confidently interacting with executives and engineers.
• Strong ownership mindset, proactively driving implementations forward independently, and structuring chaotic client environments involving undocumented workflows and conflicting teams.

Desirable Skills:

• Experience delivering SaaS, CRM/ERP, customer service, fintech, or enterprise software implementations, particularly for banks, insurers, SACCOs, telecommunications, logistics, retail, or service industries regionally.
• Proficiency in TypeScript or JavaScript, capable of understanding, modifying, testing, and debugging logic related to agent tools, API calls, workflow code, REST APIs, webhooks, authentication, and JSON payloads.
• Exposure to OpenAI, Anthropic, Gemini, vector databases, agent frameworks, Python, SQL, automation platforms such as Zapier, Make, or n8n, and familiarity with startup environments.