Testing Engineering Specialist Advisor

Role Overview

Job Description - AI Development Manager (with DevOps Understanding)

We are seeking an experienced AI Development Manager to lead the design, development, and delivery of enterprise AI and Generative AI solutions. The ideal candidate will possess strong software engineering and AI development expertise, coupled with a good understanding of DevOps practices to ensure seamless deployment, automation, scalability, and operational excellence.

The role requires technical leadership, hands-on solution architecture, stakeholder management, and the ability to lead cross-functional teams in delivering AI-powered applications on modern cloud platforms.

Key Responsibilities

• Lead the end-to-end development and delivery of AI/ML and Generative AI applications.
• Define application architecture, development standards, and engineering best practices.
• Lead teams of AI Engineers, Full Stack Developers, and Technical Leads across multiple projects.
• Design scalable, secure, and cloud-native AI solutions.
• Collaborate with Data Science, Product, QA, Infrastructure, and Security teams to deliver enterprise AI applications.
• Work closely with DevOps teams to establish CI/CD pipelines, deployment automation, release management, and production support.
• Ensure AI applications are scalable, reliable, secure, and production-ready.
• Drive Agile development practices, code quality, and engineering governance.
• Review solution designs, perform technical reviews, and mentor engineering teams.
• Manage project delivery, technical risks, and stakeholder communication.
• Promote innovation by evaluating emerging AI technologies and engineering best practices.

Mandatory Skills Experience

• 10+ years of IT experience with at least 5+ years in application development or engineering leadership.
• Proven experience delivering AI/ML or Generative AI applications in enterprise environments.
• Strong expertise in software development, system design, and cloud-native application architecture.
• Experience leading technical teams and managing enterprise-scale delivery.
• Good understanding of DevOps principles, CI/CD pipelines, containerization, and deployment automation.
• Experience working in Agile/Scrum environments.

Technical Skills

AI Generative AI

• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• AI Agents / Agentic AI
• LangChain, LlamaIndex, Semantic Kernel (or similar)
• OpenAI, Azure OpenAI, AWS Bedrock, Google Gemini/Vertex AI
• Vector Databases (FAISS, Pinecone, ChromaDB, Azure AI Search)

Application Development

• Python
• Java / .NET / Node.js (any one preferred)
• REST APIs
• Microservices Architecture
• Event-Driven Architecture

Cloud Platforms

• Microsoft Azure
• AWS
• Google Cloud Platform (GCP)

DevOps Understanding

• Git
• Azure DevOps / Jenkins / GitLab CI/CD / GitHub Actions
• Docker
• Kubernetes
• CI/CD pipelines
• Infrastructure as Code concepts (Terraform or Bicep preferred)
• Release Management and Deployment Automation

Monitoring Security

• Azure Monitor / Application Insights
• Grafana / Prometheus
• Logging Observability
• Secure Coding Practices
• DevSecOps fundamentals

Soft Skills

• Strong technical leadership and people management skills.
• Excellent communication and stakeholder management.
• Strategic thinking and problem-solving ability.
• Ability to drive delivery independently in a fast-paced environment.
• Experience managing distributed/global teams.

Preferred Qualifications

• Experience with MLOps platforms and AI model lifecycle management.
• Azure AI Engineer, AWS Machine Learning, or Google Professional ML certifications.
• Azure DevOps, Kubernetes, or Cloud certifications.
• PMP, SAFe, Scrum Master, or Agile certifications.

Key Competencies

• AI Solution Development
• Generative AI Engineering
• Software Engineering Leadership
• Enterprise Application Architecture
• Cloud-Native Development
• DevOps Collaboration
• CI/CD Deployment Automation
• Technical Leadership
• Stakeholder Management
• Agile Delivery
• Innovation Continuous Improvement
• Ownership Accountability