AI Automation Engineer
Hitachi, Ltd.2 hours ago
Bengaluru, IndiaSenior / Staff+
Responsibilities
- Design and build AI-powered and agentic solutions that automate complex, repetitive, or decision-driven Common Shared Services processes.
- Develop LLM and multimodal foundation-model applications using RAG, tool calling, structured outputs, and context engineering.
- Build, orchestrate, and govern AI agents using frameworks including LangGraph, Semantic Kernel, Microsoft Agent Framework, Azure AI Foundry Agent Service, and MCP.
- Develop APIs, integrations, and event-driven pipelines connecting AI capabilities with SAP, ServiceNow, Microsoft 365, Power Platform, data lakehouse environments, and existing automation technologies.
- Optimize models through prompt engineering, fine-tuning, distillation, and quantization.
- Establish AI evaluation and observability practices covering automated evaluations, regression testing, tracing, quality monitoring, cost governance, and performance measurement.
- Apply Responsible AI and security-by-design principles, including content safety, human oversight, prompt-injection protection, privacy safeguards, auditability, and regulatory compliance.
- Partner with stakeholders, process owners, and analysts to identify automation opportunities, assess business value, and deliver AI solutions.
- For AI Delivery, industrialize validated use cases through scalable architectures, LLMOps/MLOps, CI/CD automation, deployment standards, and production support.
- For AI Exploration, evaluate emerging technologies, conduct proofs of concept, benchmark capabilities, and prototype GraphRAG, agentic workflows, document intelligence, and multimodal AI solutions.
- Maintain documentation, architecture definitions, knowledge-sharing materials, and compliance with applicable regulations and procedures.
Requirements
- Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field; a PhD is advantageous for the AI Exploration track.
- 5–10 years of experience in software engineering, AI engineering, machine learning, or related technical disciplines.
- Experience delivering AI or Generative AI solutions into production, or building prototypes, conducting applied research, and evaluating emerging AI technologies.
- Strong Python programming skills, including testing, packaging, asynchronous programming, and software engineering practices.
- Required SQL experience; Java or C#/.NET experience is advantageous.
- Hands-on experience with LLM and agent frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, Microsoft Agent Framework, OpenAI Agents SDK, Google ADK, CrewAI, and MCP-based integrations.
- Understanding of RAG, enterprise search, embeddings, vector databases, semantic and hybrid search, re-ranking, and GraphRAG.
- Experience with Azure AI Foundry, Azure OpenAI, or other cloud AI platforms such as Google Vertex AI, Amazon Bedrock, and Databricks Mosaic AI.
- Knowledge of PyTorch, Hugging Face Transformers, PEFT, ONNX Runtime, scikit-learn, multimodal AI, intelligent document processing, OCR, speech-to-text, text-to-speech, and vision-language models.
- Knowledge of Git, Docker, Kubernetes, REST APIs, OpenAPI, gRPC, webhooks, event-driven architectures, and CI/CD practices.
- Experience with AI evaluation and observability tools such as LangSmith, Langfuse, Ragas, MLflow, promptfoo, or Azure AI evaluation services.
- Understanding of data engineering, Databricks, Spark, lakehouse architectures, orchestration, data quality, and data modeling.
- Knowledge of Responsible AI, AI governance, OWASP Top 10 for LLM applications, prompt-injection mitigation, security controls, privacy protection, and model governance.
- Strong analytical, problem-solving, communication, collaboration, and cross-functional teamwork skills.
- Curiosity about emerging AI technologies and the ability to assess sustainable business value.
- Agile experience and familiarity with Azure Boards, Jira, or similar project management tools are advantageous.
- Proficiency in spoken and written English is required.
Tech Stack
Apache SparkC#DatabricksDockerGitgRPCHugging Face TransformersJavaKubernetesMLflow.NETPythonPyTorchscikit-learnSQL
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