This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Engenheiro de Dados IA/GCP Sênior based in Brazil.
This is a senior technical opportunity focused on building and accelerating innovative AI solutions in enterprise environments.
You will work at the intersection of GenAI, AI agents, data engineering, machine learning, and cloud architecture.
The role offers hands-on ownership across experimentation, proof of concepts, architecture, development, and production.
You will design and build intelligent agents using modern frameworks such as Google ADK, CrewAI, and LangGraph.
Your work will also involve RAG, MLOps, observability, evaluation, and scalable integrations on Google Cloud.
You’ll collaborate with multidisciplinary teams in a highly innovative environment where technical exploration translates into business impact.
The position is fully remote, with the project running through December 2026 and potential for extension.
Accountabilities:
- Act as a technical reference for the engineering and experimentation of AI solutions, including GenAI prototypes, proofs of concept, and business pilots.
- Design and implement architectures for GenAI and AI-agent solutions, evaluating frameworks, tools, and patterns according to business and technical requirements.
- Build and experiment with AI agents using frameworks such as Google ADK, CrewAI, LangGraph, Semantic Kernel, or equivalent technologies, considering autonomy, tool calling, planning, and governance.
- Develop production-oriented solutions using Python, Java, and JavaScript/TypeScript, including APIs, integrations, and microservices supporting enterprise AI applications.
- Apply data engineering, Machine Learning, and MLOps practices throughout the AI solution lifecycle, from experimentation through production.
- Leverage Google Cloud Platform and its AI services as the foundation for scalable AI and data solutions.
- Define and implement evaluation criteria for AI agents and RAG systems, including quality, cost, latency, groundedness, and overall performance.
- Contribute to observability, monitoring, troubleshooting, and continuous improvement of AI and multi-agent solutions running in production.
Requirements
- Minimum of 5 years of professional experience in software or data engineering, including at least 2 years working directly with AI or GenAI initiatives.
- At least 4 years of software development experience, with strong proficiency in Python, Java, and JavaScript/TypeScript, as well as solid software engineering and production development practices.
- At least 3 years of experience with Data, MLOps, and Machine Learning concepts and practices.
- At least 2 years of experience defining, designing, and implementing GenAI architectures and solutions.
- At least 2 years of experience working with cloud environments, preferably Google Cloud Platform (GCP).
- At least 1 year of hands-on experience with AI-agent development frameworks such as Google ADK, CrewAI, LangGraph, or similar.
- Strong architectural thinking, problem-solving capabilities, and ability to translate emerging AI technologies into practical enterprise solutions.
- Strong communication and collaboration skills, with the ability to operate effectively in multidisciplinary technical environments.
Nice-to-have experience:
- 2+ years of experience with Java and the Spring ecosystem, including Spring Boot, Spring AI, or Spring Cloud.
- 1+ year of frontend development with Angular, particularly consuming AI-powered APIs.
- 1+ year of experience with RAG systems and vector databases such as Pinecone, Weaviate, Qdrant, pgvector, Azure AI Search, or equivalent technologies.
- Experience with observability and troubleshooting of AI agents and multi-agent systems in production.
- GCP or generative AI framework certifications.
Benefits
- 🏥 Medical insurance with Porto Seguro, including the possibility of coverage for spouses and children.
- 🦷 Dental insurance with Porto Seguro for employees and eligible dependents.
- 💰 Profit Sharing and Results (PLR).
- 👶 Childcare assistance.
- 🍽️ Meal and food allowances through Alelo.
- 💻 Home-office allowance to support a comfortable remote workspace.
- 📚 Partnerships with educational institutions, offering discounts and incentives for courses and degrees.
- 🚀 Support and incentives for professional certifications, including GCP, AWS, and Azure.
- 🎁 Livelo points program with flexibility in how rewards are used.
- 🏋️ TotalPass access and discounted fitness plans for employees and families.
- 🧘 Mindself wellness resources focused on meditation, mindfulness, and quality of life.
- 🌎 Fully remote work arrangement.
- 📅 Project duration through December 2026, with potential for extension.
- 📈 Opportunities to develop expertise in GenAI, cloud, data, and emerging AI-agent technologies.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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