[C297] - - Ai Engineering Manager

[C297] - - Ai Engineering Manager

31 mar
|
Mechanized AI
|
Buenos Aires

31 mar

Mechanized AI

Buenos Aires

Title: AI Engineering Manager Job Type: Full-Time Location: Remote Company Description: Mechanized AI is at the forefront of AI innovation, leveraging cutting-edge technology to transform legacy systems into modern, efficient, and scalable solutions. We work with enterprise clients to breathe life into their existing software, ensuring that they can meet the demands of today's fast-paced, digital landscape. Our team thrives on solving complex challenges and delivering innovative solutions. As an organization, we are committed to fostering an environment that encourages creativity, collaboration, and continuous learning.
Job Summary:



We are seeking an experienced AI Engineering Manager to lead our AI/ML Data Engineering team and collaborate with Cloud, Frontend, Backend, and DevSecOps teams.
Reporting to the Chief AI Officer (CAIO), this role balances technical vision and leadership with operational execution.
The AI Engineering Manager will drive AI solution development, apply the scientific process to product improvement, and ensure clear communication across teams and leadership.
They will oversee technical design & project timelines, manage requirements and features, delegate tasks, track progress, and ensure on-time delivery while mentoring talent and managing stakeholder expectations.
This hands-on leader will manage complex AI product lifecycles in a fast-paced startup, ensuring we deliver unique value to enterprise clients and strengthen our industry leadership.
Key Responsibilities: Recruit, mentor, and develop a high-performing, diverse AI/ML and Data engineering team—fostering collaboration, continuous learning, and clear performance metrics to drive retention in a fast-paced environmentChampion technical excellence by applying first principles thinking and data-driven problem solving,



enforcing rigorous code reviews, automated testing, and comprehensive documentation while promoting Agentic, MLOps, and LLMOps best practicesImplement Agile methodologies to conduct regular gap analyses and risk assessments, transforming process deficiencies into stable processesCollaborate with the CAIO to define and execute a technical roadmap that balances cutting-edge AI product development with enterprise-grade reliability, security, and performance, while integrating emerging trendsOversee the entire AI product lifecycle—from proof-of-concept through production deployment, monitoring, and iterative improvement—ensuring alignment with business objectives, client needs, and industry standardsManage product timelines, resource allocation, and deliverables through effective task management, delegation,



and milestone tracking, while maintaining high team moraleServe as an AI liaison for internal stakeholders, proactively communicating progress, identifying risks, and diffusing tensions through transparent documentation and open dialogueEmbrace a product owner mindset to prioritize tasks and manage the product backlog, aligning technical development with strategic business goalsDrive product evolution by providing insights on scalable architecture, governance, and advanced LLM/Agentic techniques, shaping a forward-thinking AI vision that anticipates future trendsEstablish and monitor clear KPIs and performance metrics through regular reviews and retrospectives to ensure accountability and continuous improvementFoster cross-functional collaboration across Data, AI, Backend, DevSecOps, QA,



and Frontend teams via structured communication and transparent reporting, ensuring cohesive alignment across the organizationCultivate innovation by promoting experimentation, calculated risk-taking, and continuous feedback loops that leverage data analytics to refine models, processes, and products Required Skills & Experience: Bachelor's in Computer Science, Software Engineering, or a related field5+ years of hands-on AI engineering (GenAI, Agents, LLMOps, MLOps, Data Science, CV, NLP, etc.
)3+ years of AI leadership experience with a dual focus on technical excellence and product management (e.g., AI Product Owner/ AI Product Manager)3+ years managing/implementing MLOps in enterprise-scale AI/ML deployments1+ years in Agentic AI implementation/management (multi-agent systems, generative AI, LLMOps)Proven ability to manage backlogs, prioritize features,



and develop product roadmaps to drive effective execution and continuous improvementExperience leveraging customer feedback and market insights (via surveys, usability tests, interviews) to refine product strategy and enhance offeringsProven ability to manage and scale remote AI/ML teams (10+ members) in dynamic, high-pressure environments with strong delegation and conflict resolutionExceptional product management, resource planning, timeline management, risk mitigation, and cross-functional alignment skillsOutstanding communication and ethical leadership with a commitment to accountability and continuous improvementProven ability to operationalize AI product management using tools like Jira and ConfluenceProficiency in English at a C2 level Preferred Qualifications: Master's, PhD, or MBA in AISolid background in cloud-native environments (e.g.,



AWS/Azure/GCP containerization, infrastructure as code).Hands-on experience taking AI Agents to productionDeep understanding of Agents (RAG, LLM best practices, security, memory management, failure points)Experience with DevOps practices, including CI/CD, containerization (e.g., Docker, Kubernetes) and infrastructure as code (e.g., Terraform, Pulumi)Experience with big data architectures on cloud platforms (e.g., EMR, Kafka, microservices, streaming/batches)Prior experience in fast-paced startups or high-growth tech companiesAdvanced proficiency in PythonPrior experience as an AI Product OwnerAdvanced expertise with LLMOpsStrong first principles thinking and adherence to AI development best practicesHigh-level understanding of UX best practicesA passion for continuous learning and staying current with emerging AI trends, cloud-native architectures, and innovative deployment methodologies Contact: Virginia KingRecruiterMechanized AI

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