Forward Deployed Engineer (AI)

Location: Remote, Krakow, Lesser Poland, Poland

Company

hirify.global builds AI-native enterprise software for asset management, operations, and critical services at global scale.

What you will do

• Embed with product teams to understand business flows, identify where AI can help, and lead technical discovery.
• Match product problems to existing AI services and help build AI-first applications on top of them.
• Gather requirements and partner with AI engineering teams to scope, design, and build new services where needed.
• Work hands-on with data pipelines, model training and serving, MLOps tooling, and product integrations.
• Ship initial versions quickly, then add monitoring, real-world feedback loops, and production-grade reliability.
• Translate stakeholder needs into AI services roadmap input and communicate technical trade-offs to product owners, business stakeholders, and engineering leads.

Requirements

• 5+ years of software engineering experience, including hands-on experience building and deploying production systems and working across unfamiliar stacks.
• Strong Python skills and willingness to work across other languages and existing customer codebases.
• Experience building and operating cloud-native services; Azure experience with AKS, Blob Storage, Key Vault, and Azure-hosted AI or model services is highly relevant.
• Production integration of LLMs and AI services, including model APIs, authentication, gateways, reliability, latency, cost, and observability.
• Experience building agentic applications with tools, APIs, and orchestration frameworks; MCP experience is strongly preferred.
• Hands-on experience designing production RAG and retrieval systems, including embeddings, vector databases, indexing, retrieval quality, and evaluation.
• Strong experience with REST APIs, authentication and authorization, external systems, data contracts, and complex integrations.
• Experience with Docker, Kubernetes, Helm, GitOps or ArgoCD, and Terraform or equivalent infrastructure-as-code tooling.
• Experience with data pipelines and relational, document, vector, and object stores; understanding of event-driven and distributed systems architecture.
• Understanding of AI evaluation, observability, monitoring, failure modes, and quality, latency, reliability, and cost trade-offs.
• Experience owning production ML or data systems rather than only notebooks or prototypes, and experience working in or alongside platform or infrastructure teams.
• Ability to work through ambiguity, communicate with non-technical stakeholders, work directly with customers, rapidly prototype, and productionize solutions.

Culture & Benefits

• Remote workplace with flexibility and hybrid work opportunities.
• Global, diverse, inclusive environment focused on collaboration, trust, innovation, and sustainability.
• Opportunity to work on AI-driven enterprise software with worldwide impact.