Senior AI/ML Engineer, GenAI, AWS

This is a fully remote position, open to applicants in Macedonia, +6 more countries.

📋 Description

• Collaborate closely with an FDE and an FDX.

• Design and deploy production GenAI systems within customer environments.

• Develop and enhance RAG systems tailored for production use cases.

• Create the evaluation framework prior to feature development.

• Write production-level code encompassing AI, backend services, and data pipelines.

• Integrate AI components into backend services and RESTful APIs.

• Deploy systems to AWS, GCP, or Azure as required by the customer, utilizing containers and CI/CD.

• Apply LLMOps and AgentOps methodologies, which include agent tracing, prompt and version management, cost and latency tracking, regression testing, and drift detection.

• Contribute to enablement and transition through documentation, runbooks, and collaboration with client engineers.

• Provide reusable components and insights back into Provectus Blueprints.

• Engage in technical discussions and participate in architectural decisions.

• Conduct model evaluations and enhance failure modes.

• Optimize model performance, efficiency, and reliability.

• Mentor junior and mid-level AI engineers.

• Perform code reviews and disseminate knowledge through documentation, presentations, and workshops.

⛳️ Requirements

• Proactive and self-motivated; seeks clarity instead of waiting for directives.

• Excellent communication and problem-solving capabilities.

• Comfortable with ambiguity and demonstrates ownership.

• Proficient in B2+ English; adept at collaborating across diverse, multicultural teams.

• Over 5 years of experience in software or ML engineering, with accountability for production systems.

• Strong foundations in AI/ML and the ability to analyze model failure modes.

• Proven experience in deploying LLM applications and agentic workflows in production.

• Familiarity with multi-step workflows, graph-based orchestration, tool utilization, state management, and recovery from partial failures.

• Experience with LLM APIs such as Anthropic, AWS Bedrock, or OpenAI, as well as agent frameworks.

• Background in developing and optimizing RAG systems in a production environment.

• Strong engineering principles; a full-stack approach across AI, backend development, and cloud infrastructure.

• Proficiency in Python and/or TypeScript.

• Practical experience with AWS in production settings, including Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar services.

• Experience in cloud-native delivery utilizing containers, ECS or Kubernetes, IaC, and CI/CD applied to AI workflows.

• Experience in building or managing an evaluation suite for non-deterministic systems.

• Knowledge in model and agent monitoring, as well as drift detection.

• Expertise in cost and latency optimization, including model tiering and caching strategies.

• Hands-on production experience with the Claude ecosystem, including Claude Code, CLAUDE.md, hooks, and skills files.

• Understanding of MCP, particularly the advantages of agent use over REST integration.

• Willingness to collaborate with distributed, multicultural teams.

🏝️ Benefits

• Remote-friendly work culture.

• Internal training initiatives with comprehensive support for Claude, AWS, and other professional certifications.

• Opportunities for conference participation.

• Career advancement; focused engineer development.

• Access to cutting-edge AI tools and premium subscriptions.

• Long-term B2B collaboration prospects.

• Private medical insurance or a budget for medical expenses.

• Paid sick leave, vacation days, and public holidays.

• Provision of equipment and all necessary technology for a comfortable and productive work environment.