Platform Engineer III

Platform Engineer III

Gautam Buddha Nagar, Uttar Pradesh

• *Job Summary**
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As the **Data \& AI Lead Engineer** , you will bridge the gap between complex data engineering and cutting\-edge artificial intelligence. You will architect, build, and scale robust data pipelines while leading the integration of Machine Learning (ML) and Large Language Model (LLM) workflows into our core products

• *Key Responsibilities**
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• *Architecture \& Core Engineering**

• **Data \& AI Infrastructure:** Design, implement, and maintain scalable, fault\-tolerant data pipelines (ETL/ELT) and MLOps frameworks to support real\-time and batch processing.
• **AI Integration:** Architect and deploy production\-grade ML models, Generative AI applications, and Retrieval\-Augmented Generation (RAG) systems.
• **Data Modeling:** Establish best practices for data warehousing, lakehouses, and vector databases to support both analytical and operational AI needs.
• **Performance Tuning:** Optimize distributed computing workloads and model inference costs for high throughput and low latency.

• *2\. Leadership \& Strategy**

• **Team Mentorship:** Guide, code\-review, and mentor a team of data and ML engineers, fostering a culture of technical excellence and continuous learning.
• **AI Roadmap:** Partner with leadership to define the company’s AI capabilities, evaluating new frameworks, tools, and SaaS providers.
• **Governance \& Compliance:** Define data governance, security policies, and ethical AI guidelines (e.g., data privacy, bias mitigation, model drift tracking).
• *Skill Requirements**
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• **Programming:** Mastery of **Python** and solid proficiency in **SQL** , **Scala** , or **Java** .
• **Data Engineering:** Deep experience with modern data stack tools like **Spark** , **Databricks** , **Snowflake** , **dbt** , and orchestrators like **Apache Airflow** .
• **AI \& Machine Learning:** Practical experience deploying frameworks like **PyTorch** or **TensorFlow** , alongside GenAI tools like **LangChain** , **LlamaIndex** , and vector databases (e.g., **Pinecone** , **Milvus** , or **Chroma** ).

• *Cloud \& DevOps:** Strong hands\-on experience with cloud platforms ( **AWS/Azure/GCP** ) and containerization ( **Docker** , **Kubernetes** ), specifically tailored for MLOps

• *Other Requirements**
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• **Bachelor’s or Master’s degree** in Computer Science, Data Science, Engineering, or a related quantitative field.
• **6\+ years** of professional experience in data engineering or software engineering.
• **2\+ years** of experience leading technical teams or acting as a principal/lead engineer.
• Proven track record of taking AI/ML models out of notebooks and successfully embedding them into production\-grade software.