Senior AI/ML Engineer (GenAI, AWS)

Location: Remote from Ukraine, Spain, Slovakia, Serbia, Armenia (Yerevan), Slovenia, or Poland

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.

What you will do

• Build and ship production GenAI, LLM-based, agentic AI, and RAG systems in customer environments.
• Work with Forward Deployed Engineers and Forward Deployed Executives to turn customer business problems into production solutions.
• Write production code across AI, backend services, data pipelines, RESTful APIs, and cloud infrastructure.
• Deploy cloud-native systems on AWS and implement LLMOps and AgentOps practices, including tracing, prompt and version management, cost and latency monitoring, regression testing, and drift detection.
• Build evaluation harnesses, investigate model failure modes, and improve performance, efficiency, and reliability.
• Create documentation and runbooks, support client handover, contribute to reusable Blueprints, mentor engineers, and participate in architecture decisions and code reviews.

Requirements

• 5+ years of software or ML engineering experience with production systems for which you were accountable.
• Solid AI/ML foundations and the ability to reason about model failure modes; experience shipping production LLM applications and agentic workflows rather than demos, POCs, or notebooks.
• Experience with multi-step agent orchestration, graph-based workflows, tool use, state management, and recovery from partial failure.
• Experience with LLM APIs such as Anthropic, AWS Bedrock, or OpenAI; agent frameworks; and production RAG systems.
• Strong engineering fundamentals with a full-stack mindset across AI, backend development, and cloud infrastructure; proficiency in Python and/or TypeScript and the ability to work productively in unfamiliar codebases.
• Production AWS experience with services such as Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, or ECR; cloud-native delivery using containers, ECS or Kubernetes, IaC, and CI/CD.
• Experience building or owning evaluation suites for non-deterministic systems, including defining measurements, producing ground truth, and setting release gates.
• Experience with model and agent monitoring, drift detection, model tiering, caching, and workload cost and latency analysis.
• Hands-on production experience with the Claude ecosystem, including Claude Code, CLAUDE.md, hooks, and skills files; ability to explain why an agent would use MCP instead of a REST integration.
• Proactive, self-directed, communicative, comfortable with ambiguity and ownership, and able to collaborate across distributed multicultural teams. B2+ English required.

Nice to have

• Experience in financial services, insurance, or healthcare; consulting, professional services, or embedded customer-facing delivery.
• AWS or Claude Code certifications.
• Experience with A2A agent-to-agent interoperability, GitHub Actions or GitLab CI, NLP, LLMs, recommendation engines, Go, TypeScript, Rust, Apache Spark, Apache Airflow, or Kafka.
• Spec-driven development experience, including writing intent, constraints, and acceptance criteria before agent implementation; experience authoring an MCP server.

Culture & Benefits

• Remote-friendly, long-term B2B collaboration in small senior teams alongside FDE and FDX.
• Internal training and support for Claude, AWS, and other professional certifications, plus conference attendance.
• Career development, access to current AI tools and premium subscriptions, and opportunities to shape delivery tooling and frameworks.
• Private medical insurance or a medical budget, paid sick leave, vacation, and public holidays.
• Equipment and technology for productive work.

Hiring process

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