Who We Are

At MAS Global Consulting, we are a premium digital engineering partner trusted by innovative startups and Fortune 100 companies, delivering high-impact solutions through agile delivery, deep technical expertise, and a strong people-first culture across the Americas.

We build long-term partnerships, not just software. MAS means “more” in Spanish, and that mindset drives our commitment to greater opportunity, inclusion, and impact.

Founded by a Latina engineer from Medellín and headquartered in Tampa, Florida, MAS Global Consulting is a 100% Hispanic and woman-owned company, recognized as a Great Place to Work and one of the Fastest-Growing Companies in the US.

Who You Are

You’re a Senior AI Engineer with a strong software engineering background and hands-on experience applying AI to improve developer productivity, reliability, and safety. You operate at the intersection of Developer Experience, applied AI, and DevOps, and you enjoy working in fast-moving, ambiguous problem spaces.

You’re curious, autonomous, and action-oriented. You prototype, evaluate, and productionize AI-assisted workflows that make engineering teams faster and more confident, while ensuring integrations are secure, auditable, and compliant with enterprise standards.

What You’ll Do

• Design, prototype, and integrate AI-assisted developer workflows such as automated code reviews, pull request drafting, and test generation.
• Build proof-of-concepts that demonstrate measurable improvements in developer speed or reliability, and evolve them into production-ready paved paths.
• Experiment with AI agent frameworks to reduce developer toil, including tasks like running tests, triaging build failures, or responding to common questions in collaboration tools.
• Evaluate and integrate third-party AI assistants and IDEs within the developer environment.
• Ensure AI integrations meet privacy, legal, compliance, and security standards, remaining secure, auditable, and reliable.
• Collaborate with Product and Analytics to instrument metrics that track AI adoption, impact on developer speed, and safety outcomes.
• Communicate insights and results that help shape the AI enablement roadmap.
• Partner with engineering teams to run AI pilots, gather feedback, and scale successful workflows into reusable solutions.
• Contribute to best-practice documentation and guidelines for responsible AI adoption.

What You Bring

• 5+ years deploying ML or AI systems to production with measurable business or operational impact.
• 2+ years architecting GenAI solutions, including LLMs, embeddings, and semantic technologies.
• Expert mastery of Python, with the ability to write high-performance, production-grade code.
• Experience working in multi-language environments (e.g., Java or Kotlin) is a plus.
• Expertise in multiple ML frameworks (PyTorch, TensorFlow) with architectural decision-making capability.
• Advanced prompt engineering, including chain-of-thought, few-shot, and multi-turn dialog design.
• Expert-level knowledge of RAG architectures: chunking strategies, hybrid search, reranking, and query optimization.
• Production experience with vector databases (Pinecone, Weaviate, Milvus, Chroma) at scale.
• Strong experience with model evaluation frameworks, evaluation techniques, and bias detection (e.g., OpenAI Evals, LangSmith, MLFlow).
• MLOps expertise: building CI/CD pipelines, monitoring systems, A/B testing frameworks.
• Production experience with at least one major cloud platform, with AWS preferred, and strong knowledge of cloud-native ML architectures.
• Excellent stakeholder management and client-facing communication skills.
• Track record of translating business requirements into successful ML implementations.
• English proficiency at B2+ level or higher.

Nice to Have

• Experience with model fine-tuning techniques (LoRA, QLoRA, PEFT, or full fine-tuning).
• Hands-on experience building multi-agent systems.
• Experience in the financial services industry.
• Prior consulting or client-facing technical experience.
• Experience leading technical initiatives.
• Solution design experience.
• Cloud or ML-related certifications.