Senior AI Engineer

Company Overview: Lean Tech is a rapidly expanding organization situated in Medellín, Colombia. We pride ourselves on possessing one of the most influential networks within software development and IT services for the entertainment, financial, and logistics sect ors. Our corporate projections offer a multitude of opportunities for professionals to elevate their careers and experience substantial growth. Joining our team means engagi ng with expansive engineering teams across Latin America and the United States, contributing to cutting-edge developments in multiple industries. Position Title: Senior AI Engineer / Forward-Deployed Engineer — Product Category: Software Development & Engineering Location: LATAM (Remote) What you will be doing: We are looking for a Senior AI Engineer / Forward-Deployed Engineer who can bridge technical and business domains, orchestrating complex deployments of our AI-driven platform for high-impact clients. You will serve as the primary technical point of contact, design scalable architectures, lead integrations across cross-functional teams, and mentor junior AI Engineers/FDEs. This is a strategic, client-facing role that combines deep software engineering expertise with strong consulting skills and the ability to influence executive stakeholders. Fluent English is essential for daily communication with international teams. Key Responsibilities: Lead discovery sessions, stakeholder meetings, executive-level workshops, and technical deep dives to understand business and operational challenges and translate them into clear technical requirements and solution architectures. Maintain ongoing weekly communication with product stakeholders, including external clients, to report progress, gather feedback, manage expectations, and ensure alignment between product development and business objectives. Translate commercial and operational needs into technical requirements, working closely with clients, Product, Engineering, and other cross-functional stakeholders. Architect and implement scalable AI-powered solutions, customizations, integrations, data pipelines, APIs, and workflow automations. Design and oversee the development of prototypes, proofs of concept, and production-ready solutions using modern software engineering, web, and AI technologies. Oversee end-to-end solution delivery, including technical execution, integrations, resource coordination, timelines, and risk mitigation aligned with client and product goals. Act as the technical liaison between clients, Product Management, Engineering, and leadership, ensuring client and stakeholder feedback is effectively incorporated into product development. Coach and mentor junior and mid-level engineers, fostering technical knowledge sharing and supporting the growth of the team. Deliver technical documentation, training, demonstrations, and knowledge-transfer sessions for client stakeholders and technical teams. Apply AI/ML and LLM technologies where appropriate to solve business problems and improve operational processes. Support the deployment and optimization of AI/ML models and LLM-based solutions when required. Must-Haves: Education & Experience: Bachelor’s degree in Computer Science, Software Engineering, Engineering, or a related technical field. 5+ years of professional software/full-stack engineering experience, including significant hands-on experience developing AI-powered solutions in professional environments. Candidates may come from AI Engineering, Software Engineering, Full-Stack Engineering, consulting, or other relevant technical backgrounds. Core Software Engineering: Strong proficiency in at least one relevant programming language or modern development stack, such as Python, JavaScript/TypeScript, React, Node.js, FastAPI, or equivalent technologies. Candidates are not required to have expertise across all listed languages and frameworks. Applied AI & Product Development: Hands-on experience building and delivering AI-powered applications or products in professional environments, with the ability to take solutions from business requirements and early-stage concepts through implementation and production. AI/ML & Automation: Strong understanding of modern AI/ML and LLM technologies, with practical experience applying AI to real-world business problems. Hands-on experience with no-code/low-code and workflow automation tools, such as n8n, Make, or equivalent platforms. Architecture, Cloud & Data: Strong understanding of modern software architecture, APIs and integrations, cloud environments, databases, and deployment practices. Experience with AWS, Azure, or GCP is acceptable; candidates are not required to specialize in a specific cloud provider. Client-Facing & Product Communication: Proven ability to work directly with external stakeholders and translate business, commercial, and operational needs into technical requirements. Strong stakeholder-management, consulting, requirements-gathering, and solution-communication skills are essential. Leadership:Demonstrated autonomy and technical leadership, including the ability to lead technical discussions, collaborate across teams, communicate progress, and mentor less-experienced engineers. Language Proficiency: C1 English required, with excellent verbal communication and the ability to clearly communicate complex technical ideas to both technical and non-technical stakeholders, including senior executives and clients. Nice to Have: Strong professional experience with Python for AI-powered application development. Experience with AWS, as it is commonly used by the team. Experience with machine-learning and LLM frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent technologies. Experience with MLOps, prompt engineering, LLM pipelines, model deployment, optimization, or fine-tuning. Experience with n8n or Make for workflow automation. Experience with microservices, serverless architectures, Docker, Kubernetes, and CI/CD. Experience with SQL/NoSQL databases, data pipelines, data governance, or web scraping. Previous experience in technical consulting, solutions engineering, startups, or product-oriented environments where engineers participate across multiple stages of solution development. AWS or other relevant cloud certifications. Familiarity with security, compliance, and data-privacy regulations. Experience contributing to recruitment, onboarding, mentoring, or growing engineering teams.