Technologist, Software Development

Position Overview

We are seeking a seasoned Senior AI Infrastructure Engineer specializing in AI-driven automation, Kubernetes orchestration, and containerized AI/ML workloads. This role focuses on architecting intelligent systems that leverage AI agentic workflows for automated product validation and testing at scale through advanced container orchestration.

Key Responsibilities

AI Workflow Architecture & Implementation

• Design and implement AI-driven test creation systems that automatically generate comprehensive test cases using machine learning models and historical data analysis

• Architect intelligent monitoring solutions leveraging AI/ML algorithms to predict system failures, optimize test coverage, and enable proactive issue resolution

• Develop autonomous testing agents capable of adaptive test execution, self-healing infrastructure, and intelligent decision-making

• Integrate large language models (LLMs), and AI decision-making frameworks into automated test orchestration workflows

• Build AI pipelines that analyze product performance data to continuously improve validation strategies

Kubernetes & Container Orchestration

• Design, implement, and optimize Kubernetes clusters specifically for AI/ML workloads and containerized testing environments

• Develop custom Kubernetes operators and controllers for AI workflow management and automated container lifecycle operations

• Architect scalable container orchestration solutions supporting both AI model inference and training workloads across diverse hardware configurations

• Implement advanced Kubernetes patterns including multi-cluster management, resource optimization, and intelligent workload scheduling

• Design container-native AI platforms with automated scaling, resource allocation, and performance optimization

• Design and implement comprehensive monitoring solutions using Prometheus, Grafana, and related CNCF tools

Technical Leadership & AI System Architecture

• Lead a team of 3-5 engineers specializing in AI/ML infrastructure, container platforms, and intelligent automation systems

• Drive architectural decisions for complex AI-driven projects involving containerized workloads and intelligent system integration

• Establish best practices for AI workflow development, container security, and MLOps processes

• Mentor team members on advanced Kubernetes patterns, AI system design, and containerization strategies for ML workloads Qualifications

Experience & Technical Skills

• BE/B.Tech/ME/M.Tech degree in Electronics & Electrical Engineering, Computer Engineering or related field

• 10-14 years of overall professional experience

• 5+ years of hands-on experience with Kubernetes in production, including custom operators, controllers, and AI/ML workload management

• 4+ years of experience implementing AI/ML workflows in production environments, particularly for automation and intelligent testing.

• 3+ years of experience in containerized application development and container orchestration for AI/ML systems

• Proven track record of leading technical teams (3-5 people) and delivering AI-driven infrastructure projects

Core Technical Competencies

• Expert-level Kubernetes expertise: K8s, Helm, custom operators, resource management, and ML-specific configurations

• Advanced AI/ML framework proficiency: TensorFlow, PyTorch, LangChain, MLflow or similar tools and AI model deployment patterns

• Strong programming skills: Python, Go, or Rust with focus on AI workflow development and container/Docker orchestration

• AI system architecture: Experience with agentic AI systems, LLM & RAG integration, and intelligent automation frameworks

Leadership & Communication

• Demonstrated ability to lead cross-functional teams focused on AI infrastructure and intelligent system development

• Strong project management skills with experience delivering AI-driven automation projects

• Excellent technical communication skills with ability to explain complex AI and container concepts to diverse stakeholders

• Experience mentoring engineers in AI system design, Kubernetes administration, and containerization best practice