Lead AI Engineer
The Lead AI Engineer will design and deploy production‑grade LLM‑based solutions, including multi‑step agents and RAG pipelines, on cloud platforms. They will also establish responsible AI guardrails, prompt‑engineering standards, and performance monitoring to ensure scalable, reliable, and cost‑effective AI services.
Skills required
About this role
- Contribute to the architecture and implementation of production-grade AI solutions leveraging LLMs, transformer-based models, RAG pipelines, and agentic systems.
- Design, develop, and optimize multi-step AI agents capable of tool/API invocation, reasoning chains, and state management.
- Support the deployment and optimization of AI-powered applications across cloud environments (AWS, Azure, or GCP), ensuring scalability, reliability, and cost-efficiency.
- Contribute to best practices for prompt engineering, evaluation frameworks, and model performance monitoring (latency, grounding, factuality, cost).
- Implement guardrails and Responsible AI practices, including prompt injection mitigation, content moderation, bias reduction, and safety controls.
- Collaborate cross-functionally with Data Scientists, Software Engineers, and Product stakeholders to take AI solutions from prototype to full production.
- Share knowledge and support other engineers in developing high-quality, modular, and maintainable Python code.
- Contribute to experimentation strategies, help define KPIs, and promote data-driven decision-making across AI initiatives.
Qualifications
- Degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience).
- Strong expertise in transformer-based models and LLM architectures.
- Proven experience designing and deploying applied machine learning or generative AI systems to production environments.
- Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, OpenAI API, CrewAI, Azure Prompt Flow, AWS Bedrock Agents, or similar tools.
- Advanced proficiency in Python and production-grade coding practices.
- Experience with containerization, CI/CD pipelines, versioning, and cloud-native architectures.
- Strong leadership skills with the ability to bridge rapid prototyping and scalable production deployment.
- Excellent collaboration and communication skills, with experience working at the intersection of Data Science and Engineering.
Additional Information
Our Perks and Benefits:
📚 Learning Opportunities:
- Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
- Access to AI learning paths to stay up to date with the latest technologies.
- Study plans, courses, and additional certifications tailored to your role.
- Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
- English lessons to support your professional communication.
🛫 Travel opportunities to attend industry conferences and meet clients.
👩🏫 Mentoring and Development:
Career development plans and mentorship programs to help shape your path.
🎁 Celebrations & Support:
- Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
- Company-provided equipment.
⚖️ Flexible working options to help you strike the right balance.
Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.
