Forward Deployed Engineer (AI/GenAI)

Location: Remote (Ukraine/Europe); typically 20–30% travel for engagement kickoffs and go-live weeks.

Company

hirify.global is a global software development services provider delivering AI-driven solutions, cloud services, and data engineering across EdTech, FinTech, and HealthTech.

What you will do

• Work directly with client teams, repositories, data, and stand-ups to identify and validate high-value AI use cases.
• Analyze business processes, data landscapes, and existing systems and translate business problems into production-ready AI architectures.
• Build, validate, deploy, and operate production LLM applications, including agents, RAG systems, and orchestration workflows.
• Integrate solutions with client APIs, identity providers, cloud platforms, messaging systems, and legacy enterprise systems.
• Implement guardrails, retries, fallbacks, human-in-the-loop checkpoints, evaluation pipelines, golden datasets, and observability.
• Participate in scoping calls, document delivery patterns, support production systems, and optimize latency, cost, security, and maintainability.

Requirements

• At least 5 years of commercial software engineering experience, with strong engineering fundamentals and the ability to adapt to different technology stacks.
• Experience shipping a production AI system for an external customer, including understanding how requirements changed between kickoff and launch.
• Fluency with at least one modern LLM platform: OpenAI, Anthropic, Gemini, Azure OpenAI, or Bedrock.
• Practical experience with RAG, vector search, embeddings, and context engineering.
• Experience building AI agents with a framework such as LangGraph, LangChain, Semantic Kernel, CrewAI, or AutoGen, including exposure to production failures.
• Ability to deploy and operate solutions on AWS, Azure, or GCP using Docker, Kubernetes, and CI/CD.
• Working knowledge of IAM, authentication, and networking.
• Ability to communicate trade-offs clearly with skeptical enterprise stakeholders.
• Upper-Intermediate English or higher.

Nice to have

• Experience with evaluation frameworks, golden datasets, regression tests, LangSmith, Langfuse, Arize Phoenix, or MLflow.
• Knowledge of AI governance, guardrails, hallucination mitigation, prompt injection, MCP, or A2A.
• Platform-level experience with Databricks, Azure AI Foundry, Bedrock, or Vertex AI.
• Consulting, solution architecture, or technical pre-sales experience.
• Experience in regulated industries such as healthcare, finance, telecom, or government.
• GitHub history, conference talks, or client-co-authored case studies demonstrating production AI work.

Culture & Benefits

• Full-time employment with a B2B contract option.
• Competitive compensation with bonuses tied to successful production go-lives.
• Remote work or work from one of the offices, with a flexible schedule.
• Certifications from Anthropic, OpenAI, AWS, GCP, and Azure, plus a professional development budget.
• Twenty covered vacation days, five additional days off, English classes, sports activities, and legal support.
• Health insurance for employees from Ukraine and a friendly, supportive work environment.

Hiring process

• Participate in client scoping calls before contract signing and provide engineering judgment on whether the solution can ship within 6–12 weeks.
• The first 90 days progress from client-embedded discovery and use-case validation to architecture, prototype validation, production deployment, evaluation, documentation, and handover.