Development Lead - AI Applications

Position Overview

Key Responsibilities

• Architecture & Design: Lead the design and implementation of scalable, maintainable full-stack applications with AI/ML components
• Code Quality: Establish and enforce coding standards, design patterns, and best practices across the engineering team
• Infrastructure: Design and implement robust development, staging, and production environments using cloud platforms (AWS/Azure/GCP)
• DevOps Excellence: Build and maintain CI/CD pipelines, automated testing frameworks, and deployment strategies
• Performance & Scaling: Optimize applications for performance, scalability, and cost-effectiveness in production environments

Team Development & Mentorship:

• Engineering Practice Establishment: Work with the team to establish robust software engineering principles, design patterns, and architectural standards that complement AI-assisted development
• Code Quality Standards: Collaborate with team members to build comprehensive code review processes that ensure maintainability, scalability, and adherence to design principles
• AI Tool & Agent Integration: Partner with the team to develop effective workflows using GenAI tools and AI Agents while maintaining code understanding and engineering rigor
• Collaborative Learning: Foster regular technical discussions, architecture reviews, and knowledge sharing sessions to elevate collective understanding
• Process Development: Work together to establish and refine development practices including Git workflows, testing methodologies, documentation standards, and deployment procedures
• Engineering Culture: Build a collaborative environment where engineering excellence and rapid AI-assisted development work hand in hand

Hands-On Development:

• Full-Stack Development: Contribute to both frontend and backend development of AI-powered applications
• AI Integration: Implement and optimize ML/Gen AI features, AI Agents, and integrations
• Technical Problem Solving: Debug complex issues and provide technical guidance on challenging problems
  

Required Qualifications

• 5-10 years of software development experience with a proven track record of delivering production applications
• Full-stack expertise with modern web technologies (React/Vue/Angular, Node.js/Python/Java, databases)
• AI/ML Project Experience: Demonstrated hands-on experience working on AI/ML projects and integrating machine learning models into applications
• Cloud Platform Proficiency: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP)
• DevOps & Infrastructure: Experience with containerization (Docker/Kubernetes), CI/CD pipelines, and infrastructure as code
• Architecture Knowledge: Strong understanding of software architecture patterns, microservices, and system design principles
• Version Control Mastery: Advanced Git skills including branching strategies, code review processes, and automation workflows

Leadership & Communication

• Technical Leadership: Experience leading technical projects and mentoring other developers
• Communication Skills: Ability to explain complex technical concepts to team members at various skill levels
• Problem-Solving: Strong analytical and debugging skills with attention to detail
• Adaptability: Comfortable working in a fast-paced environment with evolving AI technologies
  

Preferred Qualifications

• Mobile Development: Experience with iOS/Android development or React Native/Flutter
• AI/ML Technologies: Hands-on experience with frameworks such as TensorFlow, PyTorch, and Scikit-learn
• AI Agents: Proven experience building, deploying, and optimizing AI Agents for real-world business use cases
• Knowledge of vector databases and RAG implementations
• Experience in MLOps, model deployment, and lifecycle management practices
• Performance Optimization: Experience optimizing applications for high traffic and large-scale data processing
• Security Best Practices: Knowledge of secure coding practices and application security
• Client-facing Experience: Experience working in services/consulting environment with external clients
• Open Source Contributions: Active participation in open source projects or technical communities
  

What Youll Be Working On

• Building scalable AI-powered applications for clients across diverse industry sectors
• Establishing robust development and deployment pipelines for AI/ML and AI Agent applications
• Creating reusable frameworks and collaboratively developing coding standards for quality development
• Working with the team to implement comprehensive code review processes and engineering practices
• Setting up monitoring, logging, and observability solutions for production AI applications
• Collaborating with client stakeholders and cross-functional teams including data scientists and project managers
• Exploring and implementing AI Agent-based solutions to enhance client applications
• Building engineering practices and processes that scale with the teams growth and project complexity
  

Team Environment

Growth Opportunities

• Lead technical initiatives and architectural decisions
• Expand expertise in emerging AI/ML and AI Agent technologies
• Develop leadership and mentoring skills
• Opportunity to shape the technical direction of AI products
• Conference speaking and technical writing opportunities