Full Stack AI Engineer

• 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.

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.

Why Join MAS Global

• Work on meaningful AI solutions for one of the world’s leading financial institutions.
• Solve complex engineering challenges at enterprise scale.
• Build AI systems designed for real production use and measurable impact.
• Collaborate with experienced professionals across engineering, architecture, product, security, and governance.
• Grow within an inclusive, people-first organization that values technical excellence and diverse perspectives.

MAS Global Consulting is a premium digital engineering partner trusted by innovative startups and Fortune 100 companies to deliver high-impact technology solutions. We combine agile delivery, deep technical expertise, and a people-first culture to build long-term partnerships, not just software.

MAS means “more” in Spanish, and that mindset drives our commitment to creating greater opportunity, inclusion, and impact across the Americas.

Founded by a Latina engineer from Medellín and headquartered in Tampa, Florida, MAS Global Consulting is a 100% Hispanic and woman-owned company. We are recognized as a Great Place to Work and one of the fastest-growing companies in the United States.

The Opportunity

Join a high-impact engagement supporting one of the world’s leading financial institutions, where technology operates at exceptional scale and AI solutions must meet demanding standards for security, reliability, governance, and performance.

You will help build production-grade generative AI capabilities that move beyond experimentation and deliver measurable business value. This role offers the opportunity to work across RAG, agentic workflows, conversational AI, cloud-native architecture, and responsible AI within a sophisticated enterprise environment.