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Forward Deployed AI Engineer, Python, LLMs, RAG
Gramian Consulting. Work directly with business, product, and engineering stakeholders to understand complex requirements and translate them into production-ready AI solutions .
Posted 10/31/2026contractRemote • Croatia, Turkey, Czechia, Estonia, Georgia, Poland, RomaniaMid-LevelSeniorWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive expertise in building production-level AI applications using Python, LLMs, and modern web technologies. Proficient in designing robust architectures, integrating enterprise systems, and ensuring application quality and security.
Highest-signal resume keywords
Production-Level Python ExpertiseLLM-Powered Application DevelopmentLangChain, LangGraph, LlamaIndex ExperienceCloud Deployment and CI/CDEnterprise API Integration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonLLM DevelopmentLangChainLangGraphLlamaIndexReactNext.jsDockerCI/CDVector Retrieval
Soft Skills
Stakeholder CommunicationTechnical Translation
Tools & Technologies
Cloud PlatformsEnterprise APIsIAMAI AgentsAutomation Systems
Industry Keywords
Retrieval-Augmented GenerationEmbeddingsDocument PipelinesContextual RetrievalApplication Quality
Tech Stack
Tools & technologiesCloudDockerJavaScriptNext.jsPythonReact
About the role
Key responsibilities & impact- Work directly with business, product, and engineering stakeholders to understand complex requirements and translate them into production-ready AI solutions
- Design and build applications using LLMs, RAG, AI agents, tool/function calling, and structured outputs
- Develop agentic workflows using LangChain, LangGraph, LlamaIndex, or similar technologies
- Design retrieval architectures using vector search, embeddings, document pipelines, and contextual retrieval techniques
- Build robust backend services and application logic in Python
- Develop user-facing AI applications using React, Next.js, or similar frontend technologies
- Integrate AI applications with enterprise APIs, internal platforms, data systems, and authentication / IAM environments
- Deploy applications using cloud platforms, Docker, and CI/CD pipelines
- Monitor and improve AI application quality, reliability, latency, security, and business performance
- Contribute reusable engineering patterns, components, and implementation best practices across projects
Requirements
What you’ll need- 6+ years of professional software engineering experience, with strong production-level Python expertise
- Hands-on experience building LLM-powered applications in production
- Strong experience with LangChain, LangGraph, LlamaIndex, or comparable AI orchestration frameworks
- Strong understanding of Retrieval-Augmented Generation (RAG), vector retrieval, embeddings, and LLM integration patterns
- Experience designing AI agents, agentic workflows, tool/function calling, structured outputs, and automation systems
- Experience with React, Next.js, or similar modern web technologies
- Experience deploying production applications using cloud platforms, Docker, and CI/CD
- Strong understanding of enterprise integrations, secure API design, IAM, and AI / LLM-specific security considerations
- Strong ability to translate business needs into technical architecture and communicate effectively with both technical and non-technical stakeholders
- Fluent English
- Strong stakeholder communication skills