AI Engineer

Full Time, 12-25 LPA, 4-8 years, Mumbai, Maharashtra, India, Python

About Qrata

We match top talent with highly competitive career opportunities with leading startups in India and globally and address hiring challenges, recruitment brand marketing, with innovative and collaborative strategic consulting.

The AI Engineer is responsible for designing, developing, and productionizing AI capabilities that power our suite of AI Agents. You will work on integrating state-of-the-art models—including large language models (LLMs) and techniques such as retrieval-augmented generation (RAG) and agentic AI—to create intelligent, autonomous solutions. This role encompasses model fine-tuning, system integration, and deploying robust AI solutions into production environments. Your work will ensure that our products not only solve complex data challenges but also scale reliably across the P&C Insurance vertical.

·      AI Model Development & Fine Tuning:

o  Design, develop, and fine-tune AI models (e.g., LLMs) using open-source frameworks and state-of-the-art techniques.

o  Develop and implement agentic AI functionalities that enable the system to autonomously identify and execute tasks. Intelligent task orchestration execution using function calling, LLMs and agentic AI frameworks (e.g., CrewAI or Autogen or similar)" 

o  Utilize RAG techniques to integrate external knowledge sources into model outputs.

·      System Integration & Deployment:

o  Integrate AI models with data pipelines, APIs, and other system components to create end-to-end AI solutions.

o  Integrate OCR (e.g., AWS Textract) and PDF processing pipelines to convert diverse document types into high-quality data inputs.

o  Collaborate with Data Engineers to ensure that high-quality, pre-processed data is available for training and inference.

o  Develop deployment strategies for transitioning AI models from development to production, ensuring scalability and reliability.

·      Productionization & Monitoring:

o  Implement robust testing and validation procedures to ensure the performance and stability of AI models in production.

o  Monitor AI model performance and refine approaches based on feedback and emerging technologies.

o  Set up monitoring systems and implement continuous integration/continuous deployment (CI/CD) practices to maintain system performance.

o  Troubleshoot and optimize production systems to address issues such as latency, throughput, and model drift.

·      Collaboration & Innovation:

o  Work closely with cross-functional teams—including product owners, data engineers, and full-stack (ui/ux) developers—to iterate on and improve AI product features.

o  Stay current with emerging trends in AI, machine learning, and deep learning to bring innovative solutions to our product portfolio.

o  Contribute to the development of best practices and standard operating procedures

o   procedures for AI product development and deployment.

·      Strong programming skills in Python and familiarity with machine learning libraries/frameworks (e.g., TensorFlow, PyTorch).

·      Hands-on experience with large language models (LLMs), model fine-tuning, and modern AI techniques such as retrieval-augmented generation (RAG) and agentic AI.

·      Proven expertise in system integration, API development, and deploying AI models into production environments.

·      Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and CI/CD practices for scalable, production-grade systems.

·      Experience working in agile development environments and collaborating within cross-functional teams.

·      Solid understanding of data preprocessing, feature engineering, and the importance of high-quality data inputs for AI systems.

·      Educational Background:

o  Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science, or a related field.

·      Professional Experience:

o  4+ years of hands-on experience in AI/ML engineering, with a proven track record of developing, deploying, and maintaining AI systems.

o  Demonstrated experience in putting machine learning models in production and working with modern deployment tools.

·      Certifications:

Relevant certifications such as TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty, or similar credentials are a plus.

·      Additional Attributes:

o  Excellent analytical and problem-solving skills with a proactive attitude toward innovation.

o  Strong communication skills and the ability to work collaboratively in a fast-paced, agile environment.

o  A continuous learning mindset with a passion for keeping up-to-date on the latest advancements in AI technologies.