Senior ML/AI Engineer

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Design, build, and implement sophisticated agentic AI systems.

• Offer technical mentorship to junior team members.

• Work alongside production and application teams to outline the AI roadmap.

• Develop and execute agentic AI systems, which include tool-calling agents, structured reasoning, and safe action execution, while establishing security and compliance protocols.

• Spearhead the creation of evaluation frameworks for LLMs, encompassing the design of retrieval pipelines, prompt synthesis, response validation, and self-correction mechanisms.

• Engineer connections between agents and observability, incident management, and deployment systems to facilitate automated diagnostics and runbook execution.

• Partner with production and application teams to convert challenges into actionable agentic AI roadmaps, defining objective functions associated with reliability, risk mitigation, and cost-effectiveness.

• Create validator models, adversarial prompts, and policy checks; implement fallback and rollback strategies; and conduct continuous evaluations.

• Enhance cost efficiency and reduce latency through prompt engineering, context management, caching, model routing, and distillation to achieve SLOs.

• Mentor and assess the contributions of junior and mid-level engineers in agent design, evaluation methodologies, and production readiness.

⛳️ Requirements

• Extensive experience with AWS services (ECS/EKS, Lambda, S3, DynamoDB, Redshift, Step Functions, SageMaker) and infrastructure as code (Terraform/CloudFormation).

• Proficient in software development using Python, C/C++, Go, or Java, with significant experience in large-scale Python applications.

• Proven experience in designing, architecting, testing, and deploying production ML systems, including evaluation, monitoring, data pipelines, and fine-tuning workflows.

• In-depth hands-on experience with LLMs, covering API integration, prompt engineering, fine-tuning/adaptation, RAG, and tool-using agents.

• Strong comprehension of both commercial and open-source LLMs and their respective trade-offs (e.g., OpenAI, Gemini, Llama, Qwen, Claude).

• Advanced knowledge of applied statistics, core ML principles, algorithms, and data structures.

• Proficient in English, with advanced fluency.

🏝️ Benefits

• Multi-benefit card – select how and where to utilize it.

• Scholarships available for undergraduate, graduate, MBA, and language studies.

• Incentive programs for certifications.

• Flexible work hours.

• Competitive salary packages.

• Annual performance evaluations accompanied by a structured career development plan.

• Opportunities for international career advancement.

• Access to Wellhub and TotalPass.

• Private pension scheme.

• Childcare support.

• Comprehensive medical insurance.

• Dental coverage.

• Life insurance.