Senior AI/ML Engineer, GenAI, AWS

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

📋 Description

• Collaborate in tandem with an FDE and an FDX.

• Design and deploy production GenAI systems within customer environments, including cloud-native data, LLM-based, and agentic AI solutions.

• Develop and refine RAG systems tailored for production scenarios.

• Create the evaluation harness prior to feature development.

• Produce production-grade code across AI, backend services, and data pipelines.

• Integrate AI components into backend services and RESTful APIs.

• Launch systems into production on AWS, or GCP/Azure as required by the client.

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

• Assist in enablement and transition through documentation, runbooks, and collaboration with client engineers.

• Contribute reusable components and insights back into Provectus Blueprints.

• Engage in technical discussions and architectural decision-making.

• Evaluate models and enhance failure modes, performance, efficiency, and reliability.

• Guide junior and mid-level AI engineers, perform code reviews, and disseminate knowledge through documentation, presentations, and workshops.

⛳️ Requirements

• Self-motivated and proactive; seeks clarity rather than waiting for assignments.

• Outstanding communication and problem-solving abilities.

• Comfortable navigating ambiguity and taking ownership.

• B2+ English proficiency; adept at collaborating within distributed, multicultural teams.

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

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

• Experience shipping production LLM applications and agentic workflows, rather than demos, POCs, or notebooks.

• Knowledge of multi-step workflows, graph-based orchestration, tool usage, state management, and recovery from partial failures.

• Familiarity with LLM APIs like Anthropic, AWS Bedrock, or OpenAI and with agent frameworks.

• Proven experience in building and optimizing RAG systems in a production environment.

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

• Proficiency in Python and/or TypeScript.

• Direct AWS production experience, including Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar technologies.

• Experience delivering cloud-native solutions using containers, ECS or Kubernetes, IaC, and CI/CD for AI pipelines.

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

• Experience in monitoring models and agents, as well as drift detection.

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

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

• Understanding of the advantages of MCP over REST integration for agents.

• Experience in financial services, insurance, or healthcare (preferred).

• Background in consulting, professional services, or customer-facing delivery (preferred).

• AWS and Claude Code certifications (preferred).

• Knowledge of A2A interoperability (preferred).

• CI/CD pipeline experience with GitHub Actions or GitLab CI (preferred).

• Practical experience with NLP, LLMs, or recommendation engines (preferred).

• Familiarity with Go, TypeScript, or Rust (preferred).

• Experience with Apache Spark, Apache Airflow, or Kafka (preferred).

🏝️ Benefits

• A remote-friendly work culture.

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

• Opportunities to attend conferences.

• Career development focused on the growth of engineers.

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

• Long-term B2B collaboration opportunities.

• Private medical insurance or a budget for medical needs.

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

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