AI Engineer Generative AI, Real-Time Data & Hardware Testing

AI Engineer Generative AI, Real-Time Data & Hardware Testing (7 8 Years Experience)

We are looking for an experienced AI Engineer with 7 to 8 years of experience in Generative AI, Python development, real-time data processing, and hardware testing. The ideal candidate should have expertise in developing AI-driven solutions, working with streaming data, ensuring data quality, and validating hardware systems.

Key Responsibilities

• Design, develop, and deploy applications using multiple Generative AI models (LLMs, multimodal models, embedding models, etc.).
• Evaluate and integrate different GenAI models based on business use cases, performance, cost, and latency.
• Develop scalable data pipelines using Python for data processing, analytics, and AI model integration.
• Process and analyze live/streaming data to build real-time dashboards, visualizations, and alert mechanisms.
• Implement robust data quality validation processes to identify and resolve data inconsistencies.
• Perform hardware testing and validation, ensuring seamless integration between hardware devices and AI/software applications.
• Develop and execute hardware test plans, perform functional and performance testing, and troubleshoot hardware-related issues.
• Collaborate with hardware, firmware, software, and data engineering teams to validate end-to-end system functionality.
• Optimize AI applications and data pipelines for performance, scalability, and reliability.

Required Skills

• 4 5 years of experience in AI/ML, data engineering, or software engineering.
• Strong understanding of Generative AI and experience with multiple LLMs (e.g., GPT, Claude, Gemini, Llama, Mistral).
• Strong proficiency in Python for data processing, analytics, and AI application development.
• Experience with streaming data technologies such as Kafka, Spark Streaming, Flink, or similar platforms.
• Experience building real-time dashboards and visualization solutions using tools such as Grafana, Power BI, Tableau, or Streamlit.
• Strong understanding of data quality validation, data profiling, anomaly detection, and data governance.
• Hands-on experience in hardware testing, system validation, debugging, and troubleshooting.
• Experience working with hardware interfaces, sensors, embedded systems, or IoT devices is an advantage.
• Good knowledge of SQL and modern data processing frameworks such as Pandas, PySpark, or Polars.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud).
• Experience with APIs, vector databases, RAG architectures, and AI agent frameworks is a plus.

Preferred Qualifications

• Experience deploying AI solutions in production environments.
• Knowledge of MLOps/LLMOps practices.
• Strong analytical, problem-solving, and communication skills.

Communication Skills

• Excellent command of the English language (spoken and written)
• Impeccable communication skills, written, verbal, and formal presentations

Education:

Bachelor's in Computer Science is minimum required.