Leega logo
Leega

Inteligência, Inovação e Tecnologia.

AI Solutions Engineer

Solutions EngineerSolutions EngineerFull TimeRemoteSeniorTeam 201-500Since 2010H1B No SponsorCompany SiteLinkedIn

Location

Brazil

Posted

1 day ago

Salary

0

Seniority

Senior

Job Description

AI Solutions Engineer

Leega

• Conduct assessments with clients to understand business challenges, processes, pain points, and opportunities for applying Artificial Intelligence. • Act in a consultative capacity, questioning existing processes and proposing new ways of working supported by AI. • Identify, design, and prioritize AI use cases focused on delivering business value. • Design, develop, and deploy AI solutions using LLMs, intelligent agents, RAG, automations, and other modern architectures. • Develop applications using AI as an accelerator for the development cycle (AI-assisted development). • Create AI agents capable of executing tasks, integrating systems, orchestrating flows, and supporting corporate processes. • Integrate AI solutions with APIs, legacy systems, cloud platforms, and enterprise tools. • Collaborate with architects, infrastructure specialists, DevOps, and development teams to ensure scalability, security, and governance of solutions. • Participate in defining modern application architectures with a focus on AI. • Build proofs of concept (PoCs), MVPs, and production-ready solutions. • Support clients in adopting best practices for responsible AI, security, governance, and cost optimization. • Keep up with the evolution of the Generative AI ecosystem, continuously evaluating new tools, models, and frameworks. • Share knowledge through workshops, technical demonstrations, and team training.

Job Requirements

  • Experience in software development using languages such as Python, JavaScript/TypeScript, Java, Node, etc.
  • Hands-on experience with Generative AI and Large Language Models (LLMs).
  • Knowledge of developing AI agents, intelligent workflows, and AI-based applications.
  • Experience with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
  • Knowledge of RAG (Retrieval-Augmented Generation) architectures, embeddings, vector databases, and semantic search.
  • Experience consuming and integrating AI models via APIs (OpenAI, Anthropic, Google Gemini, Azure OpenAI, AWS Bedrock, among others).
  • Knowledge of modern application architectures, REST APIs, microservices, and integrations.
  • Experience with cloud environments (AWS, Azure, or Google Cloud).
  • Knowledge of DevOps practices, CI/CD, containers (Docker), Kubernetes, and deployment automation.
  • Familiarity with Git and good software engineering practices.
  • Ability to translate business needs into technical solutions.

Benefits

  • Continuous training
  • Working in a multidisciplinary team
  • Flexibility to work in dynamic environments

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