Mid-Senior AI Engineer

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 Mid Senior AI Engineer who builds, not just evaluates. You have a strong software engineering foundation and proven experience shipping AI-powered products that real users depend on daily. You operate at the intersection of Developer Experience, applied AI, and product engineering, and you thrive in fast-moving, ambiguous environments where the roadmap isn't handed to you — you help shape it. You're proactive by default. You don't wait for requirements to be perfectly defined or for someone to tell you what to build next. You identify opportunities, prototype solutions using AI-assisted workflows to iterate at speed, and drive ideas from concept to production. You use AI not just as the thing you build, but as a force multiplier in how you build — leveraging tools like code generation, automated testing, and AI-assisted development to move faster without sacrificing quality. You're comfortable working directly with product owners and stakeholders, translating their needs into technical solutions, and communicating trade-offs clearly. You take ownership of outcomes, not just outputs. What You’ll Do - Design, build, and own AI-powered internal products end-to-end — from conversational support tools to knowledge retrieval systems that serve the engineering organization daily. - Architect production RAG pipelines : embedding strategies, chunking, hybrid search, reranking, and query optimization — and own the performance in production. - Build and orchestrate AI agent workflows that streamline IT operations and internal support — including intelligent ticket routing, automated issue resolution, knowledge base retrieval, and conversational assistance for common employee requests. - Iterate rapidly using AI-assisted development workflows to go from prototype to production-ready systems in weeks, not quarters. - Partner directly with product owners to understand needs, define scope, align on priorities, and communicate progress, trade-offs, and results clearly. - Instrument adoption and impact metrics in collaboration with Product and Analytics to measure developer speed, reliability, and satisfaction outcomes. - Ensure all AI integrations meet privacy, legal, compliance, and security standards — keeping systems auditable, reliable, and aligned with enterprise requirements. - Run AI pilots with engineering teams, gather feedback proactively, and scale successful workflows into reusable, well-documented solutions. - Contribute to best-practice guidelines and internal documentation for responsible and effective AI adoption. What You Bring - 3+ years deploying software systems to production, with 1+ year building and shipping GenAI-powered products (LLMs, embeddings, semantic technologies) that real users depend on. - Demonstrated ability to take an AI feature from prototype to production-ready — including monitoring, error handling, and iteration based on real usage. - Expert mastery of Python, with the ability to write high-performance, production-grade code. Experience navigating multi-language environments (e.g., Java or Kotlin) is a plus. - Hands-on experience with RAG architectures in production : chunking strategies, hybrid search, reranking, and retrieval evaluation — not just tutorials or demos. - Prompt engineering skills: system prompts, tool use, chain-of-thought, few-shot, multi-turn dialog design, and structured evaluation of prompt quality. - Production experience with vector databases (Pinecone, Weaviate, Milvus, or Chroma) at scale. - Strong experience with model and system evaluation, with emphasis on building and maintaining eval pipelines: accuracy measurement, regression detection, hallucination tracking, and bias awareness. Production experience with evaluation platforms ( Langfuse preferred; LangSmith, OpenAI Evals , or custom frameworks also valued). - Proficiency with AI-assisted development tools and workflows — you use AI daily to accelerate your own engineering work and can demonstrate how it improves your iteration speed. - Production experience with at least one major cloud platform (AWS preferred), including deployment, monitoring, and observability of AI systems. - Strong communication and stakeholder management skills — you can explain technical decisions to product owners, flag risks early, and drive alignment without being asked. - A proactive, self-directed working style. You surface problems before they escalate, propose solutions before being asked, and take initiative to improve what's around you. - English proficiency at B2+ level or higher. - Colombian Citizen Nice to Have - Experience with model fine-tuning techniques (LoRA, QLoRA, PEFT, or full fine-tuning). - Hands-on experience building multi-agent systems and orchestration frameworks. - Experience in the financial services industry or other regulated environments. - Track record of leading technical initiatives and influencing technical direction across teams. - Prior experience working directly with product teams in a consulting or embedded engineering capacity. - Cloud or ML-related certifications.