We are looking for an AI Engineer to help build and scale a company-wide AI platform that will power customer-facing assistants, internal tools and future AI-driven products.
This role is not a data science position.
You will focus on systems, platforms, reliability and integration, ensuring AI capabilities are safe, scalable, cost-effective and reusable across teams.
Designing and building the core AI platform (gateways, orchestration, retrieval, tooling)
Integrating and operating LLMs via APIs and self-hosted solutions
Creating reusable infrastructure that enables product teams to ship AI features quickly
Implementing safety, compliance and observability for production AI systems
Partnering closely with Product, Backend, Data Science and Security teams to define AI capabilities
Build and maintain the AI Gateway for routing, rate limiting, experimentation and cost control
Develop the AI Orchestration Layer that manages prompts, retrieval, tool calls and guardrails
Design scalable APIs and SDKs for products to consume AI capabilities
Implement retrieval-augmented generation (RAG) pipelines using company data
Build document ingestion, indexing and versioning workflows
Ensure AI responses are grounded in approved and up-to-date content
Integrate with external LLM providers and manage model configurations
Implement model routing strategies based on cost, latency and use case
Work with prompt templates and system instructions to ensure predictable behavior
Implement PII handling, content moderation and prompt-injection defenses
Ensure AI systems comply with security and regulatory requirements (fintech context)
Build monitoring, alerting and fallback mechanisms for AI failures
Instrument AI systems with logging, metrics and tracing
Support evaluation workflows and feedback loops to improve quality over time
Help define SLOs and operational standards for AI in production
4+ years of experience in backend, platform or infrastructure engineering
Strong experience building production APIs and distributed systems
Experience with cloud platforms (AWS, GCP or Azure)
Solid understanding of system design, scalability and reliability
Practical experience integrating AI/ML models via APIs
Understanding of how LLMs work at a systems level (prompts, tokens, latency, cost)
Familiarity with concepts like:
Ability to reason about AI behavior, risks and trade-offs
Strong programming skills in one or more backend languages (e.g., Python, Java, Go, Node.js)
Experience with data stores (SQL, NoSQL, Redis, search engines)
Familiarity with event-driven or async architectures
Experience with observability tools (logs, metrics, tracing)
Experience building internal platforms or developer tooling
Exposure to fintech, payments or regulated environments
Experience with vector databases or search systems
Prior work on chatbots, assistants or workflow automation
Experience designing systems used by multiple teams
Product teams can ship AI features without rebuilding infrastructure
AI systems are reliable, safe and cost-controlled in production
New AI use cases plug into a shared platform with minimal effort
Leadership has visibility into AI performance, quality and impact
Build foundational AI infrastructure used across the company
Work at the intersection of AI, platforms and real business impact
Shape how AI is safely deployed in a fintech/BNPL environment
High ownership, high visibility and long-term technical impact
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Aplazo does not discriminate on the basis of race, religion, skin color, sex, gender, age, ethnic or national origin, marital status, disability, social or economic status, sexual preferences, or any other condition or characteristic. Selection is based solely on the qualifications and merits of the candidates.
