AI Engineer

hace 3 semanas


Municipio de Neuquén, Argentina DaCodes. A tiempo completo

About DaCodes We are a firm of experts in high‑impact software and digital transformation. For 10 years, we have built solutions focused on technology and innovation thanks to our team of 220+ talented #DaCoders, including developers, architects, UX/UI designers, PMs, QA testers and more. Our team collaborates on projects with clients across LATAM and the United States, delivering outstanding results. At DaCodes, you’ll have the opportunity to accelerate your professional growth, work on diverse projects across different industries, and contribute to the design, implementation and optimisation of cloud infrastructures. Our DaCoders have a major impact on the success of our business and our clients’ businesses. You will be the expert contributing to our projects, with access to disruptive startups and global brands. Requirements Design and implement AI‑powered applications and services with a strong focus on advanced RAG pipelines, vector databases, AI agents, PII/guardrails and deployments on AWS. This role requires solid full‑stack engineering experience and practical mastery of AI‑assisted development tools (Claude Code, Cursor, Lovable, Kiro). The engineer will be responsible for delivering prototypes, MVPs and production‑ready services that integrate generative models, agents and lightweight data‑preparation flows while maintaining high standards in quality, security, performance and UX. Key Responsibilities Design and implement well‑structured RAG pipelines (chunking, embeddings, retrieval optimisation). Build and orchestrate AI agents using LangGraph, CrewAI or Strands Agents. Implement security workflows: PII sanitisation, guardrails, safety layers, model validations. Integrate generative models through AWS Bedrock, Claude, Amazon Q, OpenAI or HuggingFace. Develop APIs and serverless microservices in Node.js or Python. Implement business logic, authentication, authorisation and model/service integrations. Perform necessary data preparation for AI workloads (e.g. text cleaning, normalisation, embedding generation, vector data loading). Manage vector databases at a practical level: Pinecone, Chroma, Qdrant or OpenSearch. Build functional interfaces using React / Next.js, leveraging AI‑generated components. Create lightweight dashboards or visual tools for agents, RAG flows and internal applications. Rapidly prototype interfaces using Lovable, Figma Dev Mode or similar tools. Deploy solutions on AWS (Lambda, Amplify, API Gateway, S3, CloudFront, Bedrock). Configure monitoring, logging and metrics to evaluate model behaviour and agent performance. Automate unit, integration and end‑to‑end tests using AI‑assisted tools (Claude Code, Copilot). Core Technical Skills Deep understanding of RAG: chunking strategies, embeddings, retrieval patterns, evaluation. Vector databases: Pinecone, Chroma, Qdrant or OpenSearch. AI agents: LangGraph, CrewAI or Strands Agents. Security & guardrails: PII handling, safe prompting, compliance workflows. AWS AI services: Bedrock, Comprehend or Amazon Q. Node.js or Python (≥3 years). React / Next.js (≥3 years). Claude Code (mandatory); plus Cursor, Copilot, Lovable, Kiro. API integrations, event‑driven architectures and microservices. Background & Experience Bachelor’s degree in Computer Science, Software Engineering or related field. 4‑7 years as a Full‑Stack Engineer. 1‑3 years building GenAI solutions (RAG, agents, vector databases). Demonstrated experience using AI‑assisted development tools. Benefits


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