Senior AI/ML Engineer (GenAI, AWS)

Location: Remote within North Macedonia, Bosnia and Herzegovina, Czechia, Croatia, Moldova, Bulgaria, or Montenegro

Company

hirify.global is an AWS Premier Partner and Anthropic Strategic Partner delivering applied AI applications, managed services, advisory engagements, and AI Blueprints for financial services, insurance, healthcare, and life sciences clients worldwide.

What you will do

• Work in a small senior pod with a Forward Deployed Engineer and Forward Deployed Executive.
• Build and ship production GenAI, cloud-native data, LLM-based, and agentic AI solutions in customer environments.
• Build and optimize production RAG systems, backend services, RESTful API integrations, and data pipelines.
• Develop evaluation harnesses, model and agent monitoring, tracing, prompt and version management, regression testing, drift detection, and cost and latency controls.
• Deploy AI systems on AWS using containers, CI/CD, and cloud-native infrastructure, with GCP or Azure when required by the customer.
• Document solutions, create runbooks, support client handover, contribute to reusable Blueprints, participate in architecture decisions, mentor engineers, and conduct code reviews.

Requirements

• 5+ years of software or ML engineering experience, including accountability for production systems.
• Solid AI/ML foundations and the ability to reason about model failure modes.
• Production experience shipping LLM applications and agentic workflows rather than demos, POCs, or notebooks.
• Experience with multi-step and graph-based agent orchestration, tool use, state management, recovery from partial failure, LLM APIs, and agent frameworks.
• Production experience building and optimizing RAG systems.
• Strong engineering fundamentals across AI, backend development, and cloud infrastructure; proficiency in Python and/or TypeScript and the ability to work productively in unfamiliar codebases.
• Hands-on production AWS experience with services such as Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, and ECR, or similar services.
• Experience with containers, ECS or Kubernetes, infrastructure as code, and CI/CD for AI pipelines.
• Experience owning evaluation suites for non-deterministic systems, including ground-truth creation, measured criteria, and release gates; experience with monitoring, drift detection, model tiering, caching, and cost and latency optimization.
• Hands-on production experience with the Claude ecosystem, including Claude Code, CLAUDE.md, hooks, and skills files; ability to explain MCP advantages over REST integrations.
• Proactive, self-directed, communicative, and comfortable with ambiguity, ownership, and problem-solving.
• B2+ English required for collaboration across distributed, multicultural teams.

Nice to have

• Experience in financial services, insurance, healthcare, consulting, professional services, or embedded customer-facing delivery.
• AWS or Claude Code certifications.
• Experience with A2A interoperability, GitHub Actions, GitLab CI, NLP, LLMs, recommendation engines, Go, TypeScript, Rust, Apache Spark, Apache Airflow, or Kafka.
• Experience authoring an MCP server or using spec-driven development.

Culture & Benefits

• Remote-friendly culture with long-term B2B collaboration.
• Internal training and support for Claude, AWS, and other professional certifications, plus conference attendance.
• Career growth, access to current AI tools and premium subscriptions, and participation in a growing AI delivery practice.
• Private medical insurance or a medical-needs budget, paid sick leave, vacation, and public holidays.
• Equipment and technology provided for productive work.

Hiring process

• Introductory conversation covering the role, background, aspirations, and technical questions.
• Technical interview with live engineering sessions using the candidate’s own editor; an LLM assistant may be used.
• HR interview followed by a hiring manager interview with technical questions and a possible live engineering session.