Machine Learning Engineer

About the Role We're seeking a Software Engineer to contribute to the development of AI-powered applications, intelligent automation solutions, and enterprise software platforms. This role requires strong full-stack development skills, a product engineering mindset, and hands-on experience implementing modern AI technologies including Agentic AI, Copilots, and Generative AI solutions.Key Responsibilities

• Design, develop, and enhance cloud-native enterprise applications and AI-powered solutions.
• Build modern web applications using React, TypeScript, and modern front-end frameworks.
• Develop backend services, APIs, microservices, and integration capabilities using .NET, Python, or Node.js.
• Design and implement AI Agents, Multi-Agent Workflows, and Intelligent Automation Solutions.
• Develop AI-powered assistants, copilots, and decision-support capabilities embedded into enterprise applications.
• Collaborate with product, engineering, and business teams to deliver customer-focused solutions.
• Drive engineering excellence through code quality, testing, automation, and CI/CD practices.
• Evaluate and implement emerging AI capabilities to improve business productivity and operational efficiency. Qualifications
• 3-5 years of software engineering experience with strong full-stack development expertise.
• Strong experience with React, TypeScript, JavaScript, HTML/CSS, or similar tech stack and modern UI development practices.
• Experience with backend development using .NET, C#, Python, Node.js, or Java.
• Experience building APIs, microservices, and cloud-native applications.
• Experience with Azure (preferred), AWS, or GCP, along with CI/CD and DevOps practices.
• Strong understanding of software engineering fundamentals, design patterns, and scalable application architectures.
• Familiarity with databases, data modeling, and enterprise application integrations.
• on customer value, innovation, quality, and continuous improvement. AI & Innovation Experience
• Experience with Azure OpenAI, Azure AI Foundry, Microsoft Copilot Studio, OpenAI APIs, or similar AI platforms.
• Strong experience on LLMs, Context Engineering, and Prompt Engineering to leverage foundation models for interpreting operational data, application logs, metrics, incidents, and enterprise context to generate insights and recommendations.
• Experience with Graph Correlation, Knowledge Graphs, Dependency Mapping, Event Correlation, and Causal Analysis techniques.
• Hands-on with Agent Engineering, Multi-Agent Workflows, Agent Routing, Agent Selection, Handoffs, and Orchestration Frameworks such as Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or similar technologies.
• Exposure to Model Development, Fine-Tuning, Training, Evaluation, Continuous Learning, and Performance Optimization methodologies.
• Understanding of Responsible AI, AI governance, security, and evaluation practices. Ideal Candidate A strong full-stack engineer who combines React expertise, cloud-native development, API engineering, and modern AI implementation skills to build intelligent applications, develop Agentic AI solutions, orchestrate multi-agent systems, and accelerate adoption of Generative AI across enterprise platforms and business workflows.