Artificial Intelligence Engineer

About the Role We are seeking a Senior AI Engineer Contractor based in Eastern Europe or an adjacent Central/Eastern European talent market to design, build, and deploy production-grade AI agents and AI-powered automation systems. This is a hands-on engineering role for a senior builder who can translate business problems into reliable, scalable AI systems that deliver measurable operational impact.This role sits at the intersection of software engineering, applied AI, agentic systems, data retrieval, and workflow automation. The ideal contractor is not focused on research, demos, or theoretical prototypes; they build real systems that can be used, monitored, improved, and scaled.What You Will Do Design, develop, deploy, and maintain production-grade AI agents and LLM-powered workflow automation systems.Translate ambiguous business needs into practical technical architectures, implementation plans, and working software.Build agentic workflows that use tool/function calling, memory, state management, structured outputs, APIs, and robust error handling.Implement retrieval-augmented generation capabilities, including document ingestion, chunking, embeddings, vector search, metadata filtering, retrieval evaluation, and optimization.Integrate AI systems with enterprise data sources, APIs, internal tools, workflow platforms, and cloud services.Use AI coding tools such as Cursor, Windsurf, Claude Code, GitHub Copilot, or comparable tools to accelerate delivery while maintaining production-quality standards.Optimize AI systems for reliability, cost, latency, accuracy, maintainability, security, and business value.Write clean, tested, maintainable code and participate in code reviews, architecture discussions, and technical quality checks.Set up or support basic observability, logging, monitoring, alerting, and runbooks before handoff to broader technical or operations teams.Document architecture decisions, prompts, retrieval patterns, evaluation methods, dependencies, and operating procedures so systems can be reused and scaled.Required Qualifications Senior-level professional experience building production software, preferably including AI, automation, data, or platform engineering work.Proven experience building production-grade AI agents, LLM applications, or AI-enabled workflow automation systems that execute complex, multi-step tasks.Strong hands-on experience with LLM APIs such as OpenAI, Anthropic, AWS Bedrock, or comparable enterprise LLM platforms.Experience with agent frameworks or orchestration patterns such as LangChain, CrewAI, AutoGen, LlamaIndex, custom agent architectures, or comparable approaches.Strong RAG implementation experience, including ingestion pipelines, embedding strategy, vector search tuning, retrieval quality evaluation, and performance optimization.Experience with vector databases such as Pinecone, Weaviate, pgvector, Qdrant, or similar technologies.Senior-level Python proficiency, including async/concurrent programming, clean architecture, package design, testing discipline, and production coding standards.Experience building and consuming REST and/or GraphQL APIs.Strong working knowledge of AWS services such as Lambda, ECS, Step Functions, S3, Bedrock, API Gateway, EventBridge, IAM, and CloudWatch.Working knowledge of Docker, containerization, CI/CD pipelines, Git workflows, automated testing, and code review practices.Ability to make pragmatic tradeoffs across speed, quality, scalability, cost, security, and maintainability.Excellent written and spoken English, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.Preferred Qualifications Strong JavaScript/TypeScript experience, especially for API services, automation interfaces, internal tools, or lightweight front-end workflows.Experience with Snowflake or comparable cloud data platforms.Exposure to graph-based retrieval or relational/contextual retrieval approaches, including Neo4j or comparable graph database technologies.Experience with AI evaluation frameworks, prompt/version management, synthetic test cases, observability for LLM applications, or human-in-the-loop review workflows.Experience integrating LLM systems with enterprise applications such as ticketing systems, HR systems, ERP platforms, CRM systems, knowledge bases, or workflow platforms.Background working with U.S.-based teams, distributed organizations, consulting engagements, or contractor delivery models.A portfolio, GitHub examples, architecture writeups, shipped products, or demonstrable examples of production AI systems.Contractor Profile & Working Model Comfortable operating as an independent contractor with clear deliverables, milestones, ownership, and accountability.Able to work remotely with high autonomy, disciplined prioritization, and proactive communication.Available for meaningful overlap with U.S. Eastern or Central time for stakeholder meetings, sprint ceremonies, reviews, and urgent production issues.Able to provide concise, frequent progress updates and escalate risks or blockers early.Maintains a reliable home-office setup, secure development environment, and strong confidentiality practices.Willing to participate in technical screening, architecture discussion, code review, and practical AI engineering exercises.Target Sourcing Geography Candidates should be sourced primarily from Eastern European and adjacent Central/Eastern European markets with strong software engineering and applied AI talent pools. Priority sourcing countries may include Poland, Romania, Bulgaria, Czech Republic, Slovakia, Hungary, Croatia, Serbia, Ukraine, Moldova, Lithuania, Latvia, Estonia, and comparable regional markets.What Success Looks Like Production AI agents and automation systems are delivered quickly and used by business stakeholders.Systems are reliable, observable, cost-conscious, secure, and maintainable beyond the initial build.Ambiguous business needs are converted into practical architectures and working solutions without heavy oversight.Technical decisions are clearly documented and understandable to future engineers and business stakeholders.The contractor consistently demonstrates senior engineering judgment, ownership, communication, and execution speed.Ideal Candidate Summary The ideal candidate is a senior, hands-on AI engineer from an Eastern European or Central/Eastern European talent market who can build production-grade agents and automation systems, operate independently in a remote contractor model, and deliver measurable business impact quickly. This person combines strong software engineering fundamentals with applied AI judgment, practical architecture skills, clear English communication, and a contractor mindset focused on outcomes.