
Lead Analyst
Responsibilities
Qualifications & Requirements
Experience Level: Senior Level
Full Job Description
Eaton is seeking a Lead Analyst with a strong focus on AI Engineering to join our team in Pune, India. This full-stack role requires proven experience in developing both front-end and back-end components for AI applications, including building and consuming APIs, creating customer-centric user interfaces, and designing integrations with other systems. Proficiency in .Net, JavaScript, Angular or React, and SQL is essential.
The ideal candidate will have experience deploying AI solutions by packaging trained models as services using Azure deployment services, Kubernetes, and GitHub for version control. A deep understanding of Azure AI services, such as Azure Machine Learning and Cognitive Services, along with expertise in natural language processing (NLP), computer vision, and GPT models, is required.
You will be responsible for articulating and documenting solution architecture for AI projects in collaboration with solution architects and enterprise architects. This role also involves collaborating with business leaders to understand their challenges and identify opportunities where AI can deliver significant business value. Strong analytical and problem-solving skills are crucial for translating business requirements into effective AI solutions. Excellent communication skills are necessary to explain complex AI concepts to non-technical stakeholders.
Qualifications:
- Bachelor's degree in Engineering (B.E/B. Tech) or equivalent (MCA).
- A minimum of 10 years of overall experience, with at least 5 years in solutioning and deploying end-to-end AI projects.
Technical Skills:
- .Net, JavaScript, Angular or React, SQL Server, Azure deployment services, Kubernetes, GitHub.
- Azure Cognitive Services, GPT models. GitHub Copilot is an added advantage.
- Proficiency in front-end technologies (React or Angular) and back-end technologies (e.g., Node.js, Python, .NET).
- Strong understanding of AI and machine learning frameworks (e.g., TensorFlow, PyTorch).
- Experience with cloud and hybrid infrastructures.
- Proficiency in scripting and automation tools (e.g., PowerShell, Azure CLI).
- Expertise in cloud-native development, specialized in the Microsoft Azure tech stack.
- Experience with AI use cases involving Salesforce AI (Einstein and Agentforce), ServiceNow AI (NowAssist and AI Agents), SAP AI (Joule), Oracle Cloud AI, and AI applications in Industry 4.0.
- Experience with AI platforms like Palantir, Snowflake, and DataIku is advantageous.