PJoin to apply for the strongAI/ML Engineering Lead /strong role at strongNTT DATA Europe Latam /strong /p pJoin our Agentic AI Factory as an AI/ML Engineering Leader, where you will guide a high-performing team of Agentic AI Solutions Engineers in the design, delivery, and scaling of state-of-the-art AI-driven solutions. Reporting to the Factory Manager, you will coordinate technical direction, best practices, and resource allocation, fostering ongoing innovation and technical excellence across multiple client and internal projects. /p pWhile leading by example with your own technical expertise, you will serve as the primary point of technical leadership, coaching, and escalation within the team. You will champion collaboration in translating business needs into robust, scalable, and impactful Agentic AI solutions, while partnering strategically with research, product, and operations teams. In this hands-on leadership role, you will help drive the evolution of agentic AI capabilities at the organizational level. /p h3What You'll Be Doing /h3 ol liAllocate team resources and assign projects effectively to balance workload, meet delivery deadlines, and maximize business impact. /li liOversee and guide technical solution design, architecture, and code reviews, ensuring adherence to standards for security, scalability, compliance, and responsible AI. /li liAct as the technical escalation point for complex engineering challenges, providing resolution and guidance to unblock team members. /li liMaintain strong hands-on involvement in key projects—prototyping, modeling, integration, and deployment—while developing and upskilling the team. /li liWork closely with product owners, project managers, and business stakeholders to gather requirements and translate them into actionable technical plans. /li liSupport prioritization of use cases, solution feasibility assessment, and resource planning within the engineering team. /li liFoster a culture of continuous improvement in engineering practices, DevOps/MLOps, prompt engineering, model optimization, and cloud deployment strategies. /li liDrive collaborative development of reusable components, accelerators, and best practices, helping to scale AI agent and solution delivery across the factory. /li liSupport operationalizing AI solutions, ensuring smooth integration with enterprise systems (CRM, ERP, HRIS, etc.), robust data pipelines, and consistent performance in production. /li liOversee compliance with security policies, privacy regulations, and responsible AI standards. /li liCultivate knowledge sharing, code quality, and peer learning within the team. /li liParticipate in performance evaluations, hiring, and onboarding of new Solutions Engineers. /li liKeep abreast of cutting-edge trends in agentic AI, LLMs, semantic search, and cloud technologies; drive adoption of relevant innovations in factory projects. /li liProvide clear technical and status documentation, communicate progress and risks to project leadership, and represent Solutions Engineering in cross-functional forums. /li /ol h3What You'll Bring Along /h3 ol liBachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. /li liMinimum 5-10 years in AI/machine learning engineering or software development roles, with at least 1–2 years leading (formally or informally) engineering teams or complex AI solution delivery. /li liStrong leadership and team development skills, ideally with previous team or technical lead experience (formal or informal). /li liAdvanced hands-on expertise in artificial intelligence, natural language processing (NLP), machine learning, and prompt engineering. /li liDeep proficiency in Python and major AI/ML libraries, and experience with API development/integrations in an enterprise context. /li liExperience designing, deploying, and scaling AI models and agent frameworks (LLMs/SLMs), with an appreciation for both technical depth and real-world impact. /li liFamiliarity with cloud platforms, especially Azure, AWS, or GCP, and with DevOps/MLOps practices for the AI lifecycle. /li liGood working knowledge of data pipeline engineering, and practical use of vector databases and semantic search. /li liExperience implementing and enforcing standards for secure, reliable, and compliant AI solutions (GDPR, HIPAA, etc.). /li liStrong analytical, problem-solving, and troubleshooting capabilities. /li liExcellent interpersonal and communication skills; able to explain technical details clearly to engineers and business users alike. /li liPassion for continuous learning, coaching, and fostering a collaborative, innovation-driven team culture. /li liRelevant certifications in AI, cloud technology, or engineering leadership (e.g., Microsoft Certified: Azure AI Engineer Associate, Certified ScrumMaster, or similar) are an asset. /li liDemonstrated success delivering robust agentic AI solutions in enterprise or large-scale environments. /li liHands-on experience in AI/ML model development, prompt engineering, and deployment via cloud and DevOps/MLOps practices. /li liTrack record of coaching and mentoring technical staff, and managing workload/resource allocation. /li liFamiliarity with agile methodologies and fast-paced, project-driven environments. /li liExcellent command of both spoken and written English. /li /ol h3Seniority level /h3 ulliAssociate /li /ul h3Employment type /h3 ulliFull-time /li /ul h3Job function /h3 ulliEngineering and Information Technology /li /ul h3Industries /h3 ulliIT Services and IT Consulting /li /ul pReferrals increase your chances of interviewing at NTT DATA Europe Latam by 2x /p #J-18808-Ljbffr