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Unknown · Bengaluru, India
Hiring: Engineering
What employees say
+ No pro in that low salary
− 20k salary for 14 hrs work ,cab pickup and drop worst wasting 4 hrs daily ,too much of micromanagement, arrogant attitudes of managers
More reviews on the company profile.
Interview experience · Python Developer
HCL TECH On-Campus Hiring for common role Graduate Engineer Trainer with three Domain .net/PLSQL/Python Hiring Process: 1. Round 1: Online Test 1.1. Critical Reasoning 1.2. Analytical Reasoning 1.3. Quantitativ
Average difficulty · Karūr, Tamil Nadu · 16 reports
More interview insightsJob description
Overview
AI Engineer (LLM / Generative AI/Ops)
Responsibilities
- Design and build LLM-powered applications using proprietary and open-source models.
- Implement prompt engineering, Retrieval-Augmented Generation (RAG), tool/function calling, and agent workflows.
- Deploy LLM solutions into cloud and enterprise environments with scalability and reliability.
- Build inference APIs, microservices, and CI/CD pipelines for AI applications.
- Monitor model quality, latency, cost, drift, and hallucinations in production.
- Fine-tune and enhance models using parameter-efficient techniques where required.
- Optimize inference performance using caching, batching, quantization, and prompt optimization.
- Ensure security, privacy, and responsible AI guardrails in all deployments.
- Collaborate with product, platform, and engineering teams to deliver enterprise AI solutions.
Qualifications
- Role Summary The AI Engineer will design, build, deploy, and operate production-grade Large Language Model (LLM) solutions. This role focuses on engineering rigorturning LLM capabilities into reliable, scalable, and secure enterprise applications, and continuously improving them based on performance, cost, and user feedback.
- Strong programming skills in Python; experience with backend APIs.
- Hands-on experience with LLM frameworks (LangChain, LlamaIndex, or equivalent).
- Knowledge of Docker, Kubernetes, cloud platforms, and CI/CD pipelines.
- Familiarity with LLMOps / MLOps tools and monitoring systems.
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