AI/ML Engineer (Generative AI & Agentic Systems)

Company Description

VentraGate is a cloud-focused solutions and services firm, dedicated to driving digital transformation and delivering innovative, customer-centric technologies. The company specializes in building and sustaining state-of-the-art cloud-based solutions that help businesses of all sizes become faster, more agile, and competitive. As a leading transformation consultancy, VentraGate combines technology expertise with strategic insights to create impactful solutions that meet clients' evolving needs.

Role Description

This is a full-time, on-site role based in Coimbatore. As an AI/ML Engineer specializing in Generative AI and Agentic Systems, you will design, develop, and optimize machine learning models and systems focused on generative AI technologies. You will work on implementing deep learning models, pattern recognition algorithms, and optimizing computational performance. Collaborating closely with cross-functional teams, you will contribute to the deployment and maintenance of intelligent systems and ensure they operate efficiently in real-world applications.

• Architect & Deploy: Design and deploy high-performance AI/ML models, specifically focusing on LLMs, Diffusion models, and Multimodal architectures.
• Agentic Orchestration: Develop autonomous and assistive AI agents capable of multi-step reasoning, long-term planning, and seamless tool/API usage.
• Domain Adaptation: Fine-tune (SFT, LoRA/QLoRA) and evaluate LLMs to excel in niche, domain-specific tasks while maintaining high reliability.
• System Integration: Seamlessly integrate AI services into production APIs and front-facing applications, ensuring low-latency and high throughput.
• Optimization & Benchmarking: Conduct rigorous experiments to benchmark model performance; optimize for inference speed, token efficiency, and operational cost.
• Robust Engineering: Write production-grade, modular code for ML pipelines, prioritizing observability and automated testing.
• Monitoring & Reliability: Implement LLMOps best practices, including real-time model monitoring, drift detection, and automated troubleshooting.
• Collaborative R&D: Stay at the bleeding edge of AI research, contributing to internal technical strategy and knowledge-sharing sessions.

• Experience: 23 years of hands-on experience as an AI/ML Engineer with a proven track record of shipping GenAI features.
• Core Tech Stack: Advanced proficiency in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow).
• GenAI Mastery: Deep understanding of the transformer architecture, embeddings, advanced RAG (Retrieval-Augmented Generation) patterns, and prompt optimization.
• Agentic Frameworks: Practical experience with orchestration libraries such as LangChain, LlamaIndex, CrewAI, or AutoGen.
• Vector Infrastructure: Experience with vector databases and search engines (Pinecone, Weaviate, Milvus, or Qdrant).
• Cloud & Dev Ops: Working knowledge of Docker, Kubernetes, and cloud AI services (AWS SageMaker, GCP Vertex AI, or Azure AI).
• Fundamentals: A rock-solid foundation in data structures, algorithms, and classic ML fundamentals (bias-variance trade-offs, optimization, etc.).