AI Engineer

Overview DaCodes is a high-impact software and digital transformation firm. With nearly 300 talented #DaCoders, we deliver technology- and innovation-driven solutions across LATAM and the United States. We accelerate professional growth, work on diverse projects, and design, implement, and optimize cloud infrastructures. Job Opportunity Mid‑Senior AI Engineer who can move from rapid experimentation to production‑ready AI solutions. Key Responsibilities Design and build AI‑powered solutions ranging from quick prototypes and POCs to production‑ready systems. Develop chatbots, copilots, RAG systems, agents, and AI‑driven automations. Build and iterate on AI‑based workflows using tools such as n8n or similar platforms. Decide when to prototype quickly and when to invest in production‑grade architecture. Apply prompt engineering practices suitable for both experimentation and long‑term maintenance. Integrate AI capabilities into existing systems, APIs, and workflows. Evaluate and mitigate model limitations such as hallucinations, latency, cost, and context constraints. Contribute to the transition of validated AI solutions into production environments. Collaborate closely with product, backend, frontend, and automation‑focused teams. Document technical decisions, tradeoffs, and learnings throughout the solution lifecycle. Desired Profile Mid to Senior experience as an AI Engineer, ML Engineer, or Software Engineer with strong AI exposure. Experience delivering AI solutions beyond experimentation, including production or near‑production systems. Technical Skills Strong understanding of large language models (LLMs) and their real‑world behavior. Solid programming skills in Python, Node.js, or similar backend languages. Experience building and integrating AI systems into existing architectures. Familiarity with APIs, asynchronous workflows, and event‑driven systems. Experience implementing RAG pipelines, embeddings, and retrieval strategies. Ability to build light frontend interfaces or demos using React.js when needed. AI, ML, and Data Practical understanding of machine learning concepts relevant to applied AI. Experience working with structured and unstructured data. Strong judgment to decide when an LLM‑based approach or a simpler solution is more appropriate. Cloud and Infrastructure Experience deploying AI services or prototypes in AWS, Azure, or GCP. Familiarity with containerization and cloud‑native tooling. Awareness of security, credential management, and access control for AI services. Understanding of scalability, observability, and cost considerations for AI workloads. Soft Skills Strong ownership and accountability. Comfortable balancing speed and quality. Fast learner who captures intent quickly. Proactive problem solver focused on delivery. Clear communicator of technical decisions and tradeoffs. Additional Requirements English: Advanced conversational level is highly desirable; intermediate level is acceptable and not a blocker. Location: LATAM. Work Mode: Remote. Industry: AI‑first, technology‑driven company. Nice to Have Experience with vector databases such as Pinecone, Qdrant, or similar. Experience taking prototypes or POCs into production. Exposure to open‑source LLMs or self‑hosted models. Experience building internal platforms or reusable AI components. Benefits Integration with global brands and disruptive startups. Remote work / Home office. If a hybrid or on‑site model is required, you will be informed from the first interview. Schedule aligned with the assigned project or delivery team. Monday to Friday work schedule. Day off on your birthday. Major medical expenses insurance (applies to Mexico). Life insurance (applies to Mexico). Multicultural work teams. Access to courses and certifications. Meetups with special guests from the IT industry. Virtual integration events and interest groups. English classes. Opportunities across our different business units. Proudly certified as a Great Place to Work. #J-18808-Ljbffr