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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Luxoft Usa, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Architectural Patterns, Confluence, JIRA, Directed Acyclic Graph (Directed Graphs), Extract Transform Load (ETL), Web Development, Graph Database, Python (Programming Language), Neo4j, NumPy, Scrum Methodology, Systems Development Life Cycle, Query Optimization, Next.js, Selenium, Tableau (Software), Toolchain, TypeScript, Enterprise Data Management, ReactJS, Large Language Models, Prompt Engineering, Boto3, Generative AI, Pandas, Matplotlib, Containerization, Playwright, AWS Fargate, Virtual Agents, Puppet, Terraform, GPT, Devsecops, Docker - **Published:** July 17, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=221a044944e1b41d ## About the Role 6+ years of progressive experience in engineering roles, including at least 1-2 years leading emerging tech or AI initiatives. Gen AI models (GPT, Claude, Gemini, LLaMA) and prompt engineering techniques Agentic AI, MCP, and Graph/RAG architectures Gen AI Framework (LangChain, LlamaIndex, Amazon Bedrock) Web application development using Next.js, React, TypeScript/JavaScript AWS cloud services (EC2, ELB/GLB/NLB, EKS, Fargate, Lambda, Athena, Glue, Lake Formation) Infrastructure as Code (Puppet, Terraform, Docker) and containerized deployments ETL orchestration using Apache Airflow/DAGs Vector/Graph databases (Weaviate, Milvus, PGVector, Neo4J, Neptune) and query optimization Python programming (NumPy, Pandas, Matplotlib, Boto3) Automated testing frameworks (Ragas, Playwright, Zephyr, Selenium,) Familiarity with SDLC best practices, DevSecOps, Agile Scrum/Kanban, and work management tools (JIRA, Confluence, JIRA Align). Knowledge of LLM fine tuning techniques Experience in BI tools like QuickSight, Tableau Knowledge of financial markets and enterprise data systems ## Description We are looking for an experienced AI Engineer to design and deliver scalable Gen AI solutions. The role involves building production-ready AI products using Python, React, and AWS, while leveraging modern architectures such as LLM pipelines, RAG, and agent-based systems. This role is for subcontractors. Responsibilities AI Engineer Responsibilities Lead and actively contribute to the development of AI products, pilots and solutions, with a focus on clean, maintainable code using Python, React, and AWS tools. Design, architect and build scalable Gen AI solutions, including LLM pipelines, Agentic, MCP, Graph/RAG architectures, and prompt-based applications and emerging tech. Implement cloud-native solutions using AWS services such as EKS, Lambda, Fargate, Glue, and Athena. Optimize performance of AI products, Drive continuous learning and experimentation with cutting-edge Gen AI methods, frameworks, APIs, and toolchains. Work closely with product managers, data scientists, and domain experts to define technical solutions aligned with business needs. Act as a subject matter expert (SME) on Gen AI technologies and help shape the organization's AI roadmap. Own end-to-end delivery of Gen AI solutions. Manage timelines, deliverables, and project milestones using Agile practices (Scrum/Kanban). Monitor operational metrics and incident data to drive continuous improvement and reliability. Ensure adherence to governance, DevSecOps protocols. ## Related Videos - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Make it simple, using generative AI to accelerate learning](https://www.wearedevelopers.com/videos/969-make-it-simple-using-generative-ai-to-accelerate-learning) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) - [How to Avoid LLM Pitfalls - Mete Atamel and Guillaume Laforge](https://www.wearedevelopers.com/videos/1328-how-to-avoid-llm-pitfalls-mete-atamel-and-guillaume-laforge) - [Integrate your Cognitive Assistant with 3rd-party DBs and software](https://www.wearedevelopers.com/videos/249-integrate-your-cognitive-assistant-with-3rd-party-dbs-and-software) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)