Senior AI Engineer

Ajaia is a rapidly growing AI consultancy and product studio dedicated to helping organizations move from experimentation to real results. We operate across four core pillars: AI Strategy and Advisory, AI Engineering and Automation, Workforce Training and Enablement, and Custom Product Development.

In addition to client services, Ajaia builds proprietary AI products, copilots, and vertical solutions that solve high-value industry problems. This dual model allows us to translate hands‑on implementation experience into scalable products while continuously refining our approach through real‑world deployment.

Our operating model combines deep technical execution with practical change management, enabling enterprises to deploy secure, compliant, and high‑impact solutions that drive measurable operational value. From executive road mapping to production‑ready systems and workforce upskilling, Ajaia embeds intelligent tools directly into the workflows that matter most.

Mission:
Help organizations win the AI moment.

As a Senior AI Engineer at Ajaia, you will lead the technical build of AI systems across client engagements and internal products where speed, adaptability, and execution quality matter.

You will own systems, not just features: shape architecture, make technical trade‑offs, set engineering standards, and ship production‑ready solutions across web interfaces, backend services, LLM integrations, agents, and AI‑driven workflows. You will own the infrastructure, deployment process, and security posture of the systems you lead. You will work directly with delivery leads and clients to turn vague business problems into clear technical plans.

This is a senior individual contributor role with technical leadership: you will mentor engineers, review their work, and raise the quality bar across the team.

Every role at Ajaia is AI‑forward. We expect engineers to use AI tools in daily workflows across research, implementation, debugging, testing, and documentation. AI usage is a core execution capability, not optional tooling.

• Lead the design and delivery of AI‑enabled systems for client solutions, internal platforms, and products.
• Make architecture decisions across frontend, backend, APIs, data models, AI components, cloud infrastructure, and deployment.
• Design and ship production AI capabilities: LLM integrations, RAG pipelines, agent and automation workflows, evaluation, and guardrails.
• Design and own cloud infrastructure: environments, networking, scaling, cost, and infrastructure as code.
• Own the deployment process across projects: CI/CD pipelines, release strategy, zero‑downtime deploys, and rollbacks.
• Lead application and infrastructure security: threat modeling, access control, secrets management, data protection, and security reviews for client systems.
• Set and enforce standards for code quality, testing, security, observability, and reusable engineering patterns.
• Mentor junior and mid‑level engineers through code reviews, pairing, and technical guidance.
• Work with delivery leads and clients to scope work, estimate effort, and flag technical risks early.
• Define how the team uses AI tools in development, and lead by example in daily use.
• Own production reliability: monitoring, incident response, and continuous improvement.

• 5+ years of hands‑on experience building and shipping software in professional environments.
• Deep experience with a modern frontend framework (such as React or Next.js) and a backend stack (such as Python/FastAPI or Node.js).
• Strong experience with system design, APIs, and relational databases.
• Proven experience shipping LLM‑powered systems to production (RAG, agents, tool use, evaluation, and guardrails).
• Infrastructure: deep…