Manager - AI Delivery Implementation

Job Brief

We are seeking a highly experienced and hands-on Manager AI Engineer to drive the design, development, and delivery of enterprise-scale AI solutions for our clients. This role combines technical leadership with deep engineering expertise, requiring active involvement in client solution architecture, full-stack application development, AI/ML model integration, code reviews, deployment into client environments, and engineering best practices within our AI Implementation team.

The ideal candidate will possess strong expertise in Python, Machine Learning, Cloud Technologies, and modern full-stack development, with a proven ability to lead technical teams while remaining actively engaged in coding. They should be passionate about building scalable, production-ready AI applications, mentoring engineers, establishing technical standards, and collaborating with client stakeholders, solution architects, and cross-functional delivery teams to transform client business requirements into robust, high-performance AI-powered solutions.

Mandatory Technical Skills

• 7 - 8+ years of hands-on software development experience with strong coding expertise.
• Strong programming experience in Python (Mandatory).
• Experience with Generative AI, Large Language Models (LLMs), RAG, AI Agents, and Agentic AI frameworks.
• Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks.
• Experience with Vector Databases and Enterprise AI platforms.
• Familiarity with AI-assisted development tools such as GitHub Copilot, Gemini, Cursor, or equivalent.
• Minimum 2 enterprise grade AI implementations experience.
• Proven experience in designing, developing, and deploying enterprise-grade applications.
• Strong expertise in Full Stack Development: Backend (Python, FastAPI, Flask, Django) and Frontend (React.js, Angular, JavaScript, TypeScript, HTML5, CSS3).
• Experience developing and maintaining REST APIs and Microservices.
• Hands-on experience building, training, fine-tuning, and deploying Machine Learning models.
• Experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch, and XGBoost.
• Experience deploying AI/ML solutions into production environments and implementing MLOps practices.
• Strong hands-on experience with AWS and/or Azure and/or Google Cloud Platforms (Mandatory).
• Experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes.
• Experience implementing CI/CD pipelines, DevOps, and Infrastructure as Code.
• Strong understanding of distributed systems, event-driven architecture, scalability, performance optimization, and security best practices.
• Experience working with relational and NoSQL databases.
• Strong debugging, analytical, and problem-solving skills.

Roles and Responsibilities

• Design, develop, test, and deploy scalable full-stack applications using Python and modern front-end frameworks.
• Build and deploy Machine Learning and AI-powered solutions for enterprise use cases.
• Actively contribute to coding, code reviews, debugging, and performance optimization activities.
• Develop and maintain REST APIs, microservices, and cloud-native applications.
• Design scalable, secure, and maintainable software architectures following industry best practices.
• Implement and manage CI/CD pipelines, DevOps, and MLOps processes.
• Deploy, monitor, and optimize applications and ML models on AWS and/or Azure.
• Ensure high standards of code quality through automated testing, peer reviews, and engineering best practices.
• Troubleshoot and resolve complex technical issues across application, infrastructure, and data layers.
• Drive continuous improvement in architecture, development processes, security, scalability, and operational efficiency.
• Mentor and guide team members on technical design, coding standards, and engineering best practices.
• Stay updated with emerging technologies and recommend innovative solutions to enhance products and platforms.
• Work in Agile teams and contribute to sprint planning, estimation, and successful delivery of project milestones.
• Customize and configure AI/ML solutions to meet specific client technical environments, data landscapes, and integration requirements.
• Partner with client IT and delivery teams during UAT, go-live, and post-production support to ensure smooth solution adoption.
• Support solutioning and technical estimation during pre-sales and proposal stages for client engagements.

Experience & Education

• 8-12 years of overall experience.
• Master's or Bachelor's degree in Computer Science or an Engineering discipline.