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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Full Stack AI Engineer - **Company:** MAS Global Consulting - **Location:** Plano, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Software Quality, Code Review, Information Systems, Continuous Integration, Distributed Systems, Amazon DynamoDB, Python (Programming Language), Cloud Services, Search Technologies, Software Deployment, Software Engineering, TypeScript, Speech Recognition, Enterprise Data Management, Enterprise Software Applications, Chatbots, ReactJS, Large Language Models, State Machines, Generative AI, Backend, Web Filtering, Event Driven Architecture, Containerization, AngularJS, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Graphql, Speech Synthesis, Front End Software Development, Api Design, Api Gateway, Restful APIs, Amazon Simple Queue Service (SQS), Automation Anywhere, Docker, Microservices - **Published:** September 21, 2026 - **Apply:** https://www.disabledperson.com/jobs/75354653-full-stack-ai-engineer ## About the Role You are an experienced software engineer who has successfully expanded into AI/ML and generative AI while maintaining strong production engineering fundamentals. You are comfortable turning complex business needs into scalable technical solutions, from architecture and system design through hands-on development and deployment - including both backend services and the user-facing frontend that consumes them. You understand how to build reliable RAG pipelines, integrate foundation models, connect AI applications to enterprise systems, and deliver software that performs in real production environments, end to end. You bring sound engineering judgment, curiosity, and a collaborative mindset. You do not need to have worked with every technology listed below, but you should have relevant production experience and the ability to transfer your knowledge across platforms and frameworks., * Bachelor's degree in computer science, engineering, information systems, or a related field. * Seven or more years of professional software development experience using Java or Python. * At least two years of hands-on experience building and deploying AI/ML or generative AI applications in production. * 2+ years of hands-on experience building frontend interfaces (e.g., React, Angular, or similar) that integrate with backend services and APIs, with demonstrated ability to own features end to end. * Strong understanding of RAG architectures, including chunking, embeddings, retrieval strategies, and vector databases. * Experience integrating large language models through APIs or managed cloud services. * Experience building AI workflows or agents that use tools, enterprise data, APIs, or multiple processing steps. * Strong understanding of API design, microservices, distributed systems, and production software engineering. * Practical experience with cloud services, CI/CD, containerization, and production deployments. * Ability to evaluate architectural tradeoffs and communicate technical decisions clearly. * A strong commitment to software quality, security, observability, and responsible AI. Experience That Will Help You Stand Out * AWS Bedrock and Anthropic Claude models. * AWS services such as Lambda, Step Functions, API Gateway, S3, DynamoDB, and SQS. * LangChain, LlamaIndex, Semantic Kernel, CrewAI, or comparable orchestration frameworks. * Pinecone, OpenSearch, pgvector, FAISS, or other vector search technologies. * LLM evaluation frameworks, tracing, observability, and quality measurement. * Guardrails, content filtering, prompt-injection defenses, and responsible AI controls. * Docker, ECS, EKS, Kubernetes, and infrastructure as code. * Experience with React, TypeScript, or modern frontend build tooling. * REST, GraphQL, and event-driven architectures. * Speech-to-text, text-to-speech, or voice-enabled AI applications. * Experience delivering technology within financial services or another highly regulated industry. ## Description * Develop RAG pipelines involving document processing, chunking, embeddings, retrieval, reranking, and vector storage. * Build agentic workflows that connect foundation models with enterprise data, APIs, tools, and business processes. * Integrate large language models through managed services and model invocation APIs. * Develop effective prompting strategies using system instructions, few-shot prompting, tool calling, structured outputs, and context management. * Build reliable full-stack applications, including backend services and APIs using Java or Python, and the frontend interfaces that expose them to end users. * Contribute to scalable microservices, distributed systems, and event-driven architectures. * Develop conversational AI experiences, including intelligent assistants and chat-based applications. * Collaborate on cloud deployments, CI/CD pipelines, containerization, infrastructure automation, monitoring, and production support. * Establish evaluation methods for measuring AI quality, reliability, safety, and business performance. * Implement guardrails, content controls, observability, and responsible AI practices. * Partner with product, architecture, engineering, security, and governance teams throughout the delivery lifecycle. * Contribute to architecture discussions, code reviews, technical decisions, and hands-on problem-solving. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Supercharge your cloud-native applications with Generative AI](https://www.wearedevelopers.com/videos/950-supercharge-your-cloud-native-applications-with-generative-ai) - [Meet Your New BFF: Backend to Frontend without the Duct Tape](https://www.wearedevelopers.com/videos/682-meet-your-new-bff-backend-to-frontend-without-the-duct-tape) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)