Technical Architect - Manager

Location: Bengaluru   •   Experience: Senior Level   •   Openings: 1
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Job description

Role Overview
AI and ML Tech Stack, you will drive impactful AI initiatives and focus on delivering business outcomes through innovative artificial intelligence and machine learning solutions. You will be a key member of the AI Enablement team, collaborating with product management, data engineering, software development teams, and business stakeholders. You will have the autonomy to lead, innovate, and improve AI capabilities while upholding our commitment to quality and continuous learning.
 
Responsibilities
Lead the end-to-end design, development, and deployment of scalable AI and Machine Learning solutions.
Define and implement best practices, standards, and governance frameworks for AI development and deployment.
Collaborate with cross-functional stakeholders to align AI initiatives with business objectives and enterprise strategy.
Drive innovation across AI domains, including Natural Language Processing (NLP), Computer Vision, Generative AI, and Reinforcement Learning.
Conduct research and evaluate emerging AI technologies, tools, and methodologies to enhance organizational capabilities.
Mentor and guide AI engineers, developers, and data scientists, fostering a culture of technical excellence and continuous learning.
Communicate complex AI concepts to technical and non-technical stakeholders and provide actionable insights through data-driven decision-making.
Oversee AI operationalization, model deployment, scalability, and performance optimization across enterprise environments.
Promote the adoption of AI tools, platforms, and methodologies across business functions.
 
Skill Set
12+ years of hands-on experience in application design, software engineering, and technology solution delivery.
Proven expertise in Python programming for AI and Machine Learning applications.
Strong experience with Machine Learning and Deep Learning algorithms, including supervised, unsupervised, and reinforcement learning techniques.
Hands-on expertise with AI frameworks and platforms such as TensorFlow, PyTorch, and related ecosystems.
Strong understanding of data analysis, data preparation, feature engineering, and data visualization techniques.
Experience in Natural Language Processing (NLP) technologies and solutions.
Knowledge of cloud platforms and scalable AI architectures, including AWS and Big Data technologies.
Experience with AI infrastructure, model deployment, MLOps, and DevOps practices.
Understanding of AI security principles, threats, and mitigation strategies.
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
Strong communication, stakeholder management, and mentoring skills.
Relevant AI and Machine Learning certifications.