About this role
The Artificial Intelligence Manager will help develop and implement the EisnerAI Platform, which supports intelligent solutions across tax, audit, outsourcing and advisory services. The role supports the platform’s technical architecture and leads developers and engineers working on the EisnerAI Agent Workforce. The preferred location is Mumbai.
Responsibilities
- Integrate the platform’s data management, governance, AI, agents and application layers. Design agentic frameworks for initiation, execution, state management, logging and error handling.
- Contribute to model evaluation frameworks and post-training optimization for custom LLMs and AI agents. Work with senior architects and stakeholders to design and implement scalable AI solutions.
- Lead and mentor a technical team; participate in technical, code and solution-design reviews; coordinate cross-functional delivery; and uphold data governance policies and responsible AI practices.
Required qualifications
- Bachelor’s degree in Computer Science, Engineering, Data Science or a related technical field. At least 6 years of software development experience, including at least 2 years in AI/ML solution architecture or technical leadership, plus at least 2 years of hands-on experience with Azure cloud services and enterprise-scale solutions. Experience leading small to mid-sized technical teams or managing project deliverables.
- Hands-on expertise with Microsoft Azure AI Foundry and Azure AI services; Azure OpenAI Service, GPT models, prompt engineering and fine-tuning; Azure AI Search for vector and semantic search and knowledge mining; and Azure Databricks for data engineering and machine learning model development.
- Proficiency in at least one of Python, C#, JavaScript/TypeScript or SQL; understanding of AI solution design and enterprise application integration; and communication and stakeholder-management skills.
Preferred qualifications
- Master’s degree in Computer Science or AI/ML, or an MBA with a technical focus. Experience with Azure Machine Learning, MLOps, model deployment and monitoring; Azure Cognitive Services, including Document Intelligence, Language Understanding and Computer Vision; TensorFlow, PyTorch, Scikit-learn or Hugging Face Transformers; vector databases such as Azure Cosmos DB, Pinecone or Weaviate; Azure DevOps, GitHub Actions, Docker or Kubernetes; and Agile/Scrum delivery.
Skills for this role
Microsoft Azure AI FoundryAzure AI ServicesAzure OpenAI ServiceGPT modelsPrompt engineeringFine-tuningAzure AI SearchVector searchSemantic searchKnowledge miningAzure DatabricksData engineeringMachine learningPythonC#JavaScriptTypeScriptSQLAI solution architectureEnterprise application integrationAI agentsAgentic frameworksModel evaluationPost-training optimizationData governanceResponsible AITechnical leadershipTeam mentoringStakeholder managementAzure Machine Learning