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Engenheiro de software de ia

São Paulo do Potengi
Exadel
Engenheiro software
Anunciada dia 26 agosto
Descrição

Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. Job Overview We are seeking a skilled AI Engineer to join our innovation-driven team. This role involves designing intelligent agents, building advanced prompts and knowledge bases, and developing AI/ML solutions that drive automation and business transformation. You'll work autonomously with cutting-edge tools and have the freedom to experiment and evolve your approach. What You’ll Do Design, implement, and manage AI agents, including the development of advanced prompts and knowledge bases Build and maintain robust data pipelines for AI-driven solutions Develop process automation using both traditional and generative AI techniques Continuously test, refine, and optimize models, prompts, and agents to ensure performance and scalability Act autonomously in selecting technologies and methodologies, providing technical justification Stay up to date with advancements in data science, AI, and ML, proactively identifying opportunities to apply them to business challenges Formulate hypotheses, run experiments, validate concepts, and apply appropriate metrics to measure results What You Bring Bachelor’s degree in Engineering, Computer Science, Mathematics, or related fields Strong experience in Python (preferred), SQL, and/or Java/Scala Familiarity with frameworks like Fast API, Flask, or Django Deep understanding of both traditional and generative AI techniques applied to complex business problems Hands-on experience with AWS solutions, especially AWS Bedrock and Sage Maker Proven experience in prompt engineering, management, and optimization Advanced knowledge of prompting techniques: few-shot learning, chain-of-thought, self-consistency, prompt chaining, guardrails Experience building and utilizing knowledge bases to support AI solutions Full project lifecycle experience in ML/AI projects, from prototyping to deployment Familiarity with platforms such as Hugging Face, Open AI, Lang Chain, or similar Knowledge of MLOps and tools such as MLflow, Databricks, Vertex AI, or Sage Maker Experience in projects involving NLP, copilots, content generation, or task automation using generative AI

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