FDE AI/Solutions Architect (AI, Python/Data)

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

Company

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

What you will do

• Work with clients and Forward Deployed Executives to understand business functions, identify underlying problems, and redesign workflows from first principles.
• Design and ship production GenAI, LLM-based, agentic AI, and RAG systems in customer environments.
• Build evaluation harnesses, define quality criteria, instrument systems, and use evaluation results to guide development and releases.
• Write production code across AI, backend services, and data pipelines, deploying containerized systems with CI/CD, testing, monitoring, and infrastructure on AWS or another required cloud.
• Lead architecture reviews, technical proposals, scoping, design documentation, standards, mentoring, and knowledge sharing.
• Own technical direction and customer adoption while measuring engineering outcomes against business KPIs and transferring systems to clients.

Requirements

• Proactive, self-directed, and comfortable with ambiguity, ownership, and underspecified engagements.
• B2+ English and confidence collaborating across distributed, multicultural teams.
• Ability to understand client-side work before coding, communicate with business-unit leaders and CTOs, present outcomes, and create phased delivery plans with deliverables, dependencies, risks, and cost estimates.
• 7+ years of experience building and running production systems.
• Solid AI/ML foundations, including reasoning about model capabilities and failure modes.
• Production experience designing and shipping LLM applications, agentic workflows, multi-step and graph-based orchestration, 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 proficiency in Python and/or TypeScript and the ability to work productively in unfamiliar codebases or languages.
• Experience making and defending architectural trade-offs; hands-on AWS production depth including Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar.
• Cloud-native AI delivery using containers, ECS or Kubernetes, infrastructure as code, and CI/CD; experience with model and agent monitoring, drift detection, cost control, latency optimization, model tiering, and caching.
• Ownership of an evaluation suite for a non-deterministic system, including ground truth, measured criteria, and release gates.
• Hands-on Claude ecosystem experience including Claude Code, CLAUDE.md, hooks, and skills files; ability to explain MCP versus REST integration.

Nice to have

• Founder, CTO, or engineering leadership experience with a return to individual contribution.
• Experience in financial services, insurance, healthcare, consulting, professional services, or embedded customer-facing delivery.
• Knowledge of A2A interoperability, AWS or Claude Code certifications, and CI/CD pipelines using GitHub Actions or GitLab CI.
• Experience with Go, TypeScript, Rust, Apache Spark, Apache Airflow, or Kafka.
• Experience authoring an MCP server and using spec-driven development.

Culture & Benefits

• Remote-friendly culture with long-term B2B collaboration.
• Work in small, senior teams alongside Principal Architects and Forward Deployed Engineers.
• 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 support for building internal tooling and frameworks.
• Private medical insurance or a medical budget, paid sick leave, vacation, public holidays, and equipment.

Hiring process

• Introductory conversation covering the role, background, aspirations, and technical questions.
• Technical interview with live engineering sessions using real problems and the candidate’s 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.