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SymphonyAI - Lead AI Delivery Engineer - Python

Symphonyincubator Business Services
8 - 10 Years
Bangalore

Posted on: 04/11/2026

Job Description

Introduction :

SymphonyAI Industrial is a leading provider of Artificial Intelligence-driven solutions that optimize the health, reliability, and operational performance of industrial assets and processes.

Our cutting-edge IRIS platform combines Predictive AI, Generative AI, and Agentic AI capabilities to deliver real-time insights, predictive intelligence, and prescriptive recommendations across asset-intensive industries.

We are seeking an experienced Lead AI Delivery Engineer to drive the successful implementation of Predictive AI, Machine Learning, Generative AI, and Agentic AI solutions for industrial customers globally.

Responsibilities :

- Customer Engagement & Solution Delivery

- AI & Machine Learning Implementation

- Agentic AI & Generative AI Delivery

- Project Leadership & Stakeholder Management

- Customer Success & Post-Deployment Support

- Technical Leadership

Required Skills & Qualifications :

- Bachelors or Masters degree in Engineering, Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, or related discipline.

- 8+ years of experience in customer-facing technology delivery, industrial software implementation, or AI project delivery.

- 3+ years of hands-on experience in AI, Machine Learning, Advanced Analytics, Data Contextualization, or Data Science projects.

Tech Stack :

- Python, Scikit-learn, TensorFlow, PyTorch, Keras, NumPy, Pandas.

- Generative AI, Agentic AI, RAG, Vector Databases, Multi-Agent Systems.

- LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI Assistants, MCP.

- Azure AI, Azure OpenAI, AWS Bedrock, Google Vertex AI, Databricks.

- Power BI, Tableau, Plotly, Matplotlib.

Preferred Skills & Qualifications :

- Predictive Maintenance, Reliability Engineering, Asset Performance Management, Digital Twins, Industrial IoT Platforms, Enterprise Generative AI Deployments, LLMOps and MLOps.

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