Apply for NiCE Off Campus Drive 2025! Hiring Software Engineer Job in Pune for 1+ Years. BE/BTech/ME/MTech grads build GenAI Ops pipelines, LLM deployment, Azure AI/ML, MLOps with Python/.NET, Docker/K8s for scalable AI solutions.
Candidates who are interested in NiCE Off Campus Drive Job Openings can go through the below to get more information.
Key Job details of Software Engineer job
Company: NiCE
Qualifications: BE/BTech/ME/MTech
Experience Needed: 1+ Years
Location: Pune
Job Description
We are looking for a Software Engineer to join our AI Engineering team, focusing on building and operationalizing AI/ML and Generative AI solutions. In this role, you will design and implement robust software systems that enable MLOps and GenAI Ops workflows, ensuring scalable, secure, and efficient deployment of AI models and applications. You will work closely with data scientists, prompt engineers, and cloud specialists to deliver production-grade AI services using Azure AI and AI Foundry.
How will you make an impact?
Design and implement GenAI Ops pipelines for LLM deployment, fine-tuning, and inference optimization.
Automate prompt lifecycle management, versioning, and evaluation.
Integrate Azure AI services and AI Foundry for scalable GenAI solutions.
Build CI/CD workflows for LLM-based applications, including containerization and orchestration.
Implement observability and monitoring for LLM performance, latency, and hallucination detection.
Collaborate with Data Scientists and Prompt Engineers to streamline GenAI workflows.
Ensure compliance with Responsible AI, data privacy, and model governance.
Have you got what it takes?
Cloud Platforms: Strong experience with Azure AI, Azure ML, and Azure DevOps.
GenAI Tools: Hands-on with AI Foundry, OpenAI/Azure OpenAI APIs, or similar platforms.
Programming: Proficiency in .Net or Python; experience with prompt engineering frameworks.
CI/CD: Familiarity with Azure DevOps pipelines, Docker, Kubernetes.
Monitoring: Knowledge of LLM observability tools and metrics for GenAI (e.g., prompt success rate, token usage).
Understanding of MLOps principles and GenAI Ops best practices.
Qualifications:
Bachelor’s or master’s degree in computer science or a related field.
Experience with fine-tuning LLMs and embedding models.
Knowledge of vector databases (e.g., PostgressPGE Vector, Azure Cognitive Search).
Familiarity with RAG (Retrieval-Augmented Generation) architectures.
How to Apply NiCE Off Campus Drive 2025
Click on Apply to Official Link NiCE Below – You will go to the Company Official site
First of all Check, Experience Needed, Description and Skills Required Carefully.
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Interview Questions
- Describe designing GenAI Ops pipelines for LLM deployment and inference.
- How do you implement prompt lifecycle management and evaluation?
- Explain integrating Azure AI Foundry with OpenAI APIs in production.
- Walk through building CI/CD for LLM apps using Azure DevOps/Docker/K8s.
- What metrics do you monitor for LLM performance and hallucination detection?
- Describe MLOps/GenAI Ops best practices for model governance.
- How do you implement RAG with vector databases like Postgres PG Vector?
- Explain fine-tuning LLMs and embedding models for specific use cases.
- What Responsible AI and data privacy practices do you follow?
- Describe collaborating with Data Scientists on production AI workflows.
Selection Process
- Online application via NiCE careers portal.
- Resume screening for Azure AI/ML and GenAI experience.
- Technical assessment on Python/.NET, cloud, MLOps concepts.
- Technical interviews on LLM pipelines, RAG, observability.
- Behavioral round on collaboration and innovation.
Pro Tip
Build a RAG demo with Azure OpenAI, vector DB, and CI/CD pipeline on GitHub. Practice explaining LLM observability metrics and Responsible AI governance.