Role Overview

We are seeking a highly skilled Senior AI Engineer with 4-6 years of experience to design, build, and deploy advanced AI-driven solutions that transform real estate investment and decision-making.

This is a hands-on technical role focused on building scalable AI systems, implementing advanced machine learning techniques, and deploying production-grade AI applications in modern cloud environments.

The ideal candidate combines deep expertise in LLMs, advanced ML techniques, RAG pipelines, and scalable AI system design, along with strong software engineering fundamentals to build AI based products for our organization.

Key Responsibilities

- Advanced AI System Development: Design and develop production-grade AI applications using LLMs, Generative AI, and machine learning models.
- Advanced AI System Development: Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases.
- Advanced AI System Development: Develop AI agents and workflow automation systems for document intelligence, market analysis, and underwriting workflows.
- Advanced AI System Development: Apply advanced AI techniques including prompt engineering, fine-tuning (LoRA, adapters), embedding strategies, and model benchmarking.
- Advanced AI System Development: Evaluate models for accuracy, latency, robustness, and business impact.
- Advanced AI System Development: Have full stack development experience to build products.
- Backend AI Infrastructure Engineering: Build scalable backend services and APIs (Python preferred).
- Backend AI Infrastructure Engineering: Integrate AI models into production-ready applications.
- Backend AI Infrastructure Engineering:



Develop data ingestion, preprocessing, and feature engineering pipelines.
- Backend AI Infrastructure Engineering: Ensure observability, logging, monitoring, and reliability of AI systems.
- Backend AI Infrastructure Engineering: Optimize systems for performance and cost efficiency.
- Model Lifecycle MLOps: Implement model versioning and experiment tracking.
- Model Lifecycle MLOps: Build automated evaluation and validation pipelines.
- Model Lifecycle MLOps: Support continuous improvement via A/B testing and feedback loops.
- Model Lifecycle MLOps: Ensure AI practices including explainability and bias mitigation.
- Cross-Functional Collaboration: Partner with product, data, and engineering teams to translate business requirements into scalable AI solutions.
- Cross-Functional Collaboration: Contribute to architecture discussions and code reviews.
- Cross-Functional Collaboration: Mentor junior engineers and promote AI engineering best practices.

Required Qualifications

- 4-6 years of experience in AI/ML engineering or software engineering with strong AI exposure.
- Strong proficiency in Python and up-to-date ML frameworks (PyTorch, TensorFlow, or similar).
- Hands-on experience with LLMs, Generative AI systems, RAG pipelines, and vector databases.
- Experience deploying AI solutions in production environments.
- Strong understanding of scalable system design and distributed systems.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior AI Engineering Professional (Bengaluru)
🏢 Pretium Partners
📍 Bengaluru