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hirist

Generative AI Developer - NLP/LLM

SMARTWORK IT SERVICES
Anywhere in India/Multiple Locations
4 - 6 Years

Posted on: 27/08/2025

Job Description

Job Title : Gen-AI Developer

Experience : 4 - 6 Years

Location : Pan India

Role Overview :


We are looking for an experienced Gen-AI Developer with a strong background in C#, Semantic Kernel, and Azure AI services to design, build, and deploy next-generation AI applications leveraging Large Language Models (LLMs), Agentic AI, and MLOps practices. The ideal candidate should bring a mix of hands-on development, infrastructure management, and AI orchestration expertise to create scalable, secure, and cost-optimized Gen AI solutions.


Key Responsibilities :


AI Application Development :


- Design, develop, and optimize LLM-powered applications using C#, Semantic Kernel, and .NET Aspire.


- Implement AI agent architectures for conversational AI, decision-making, and automation workflows.

- Build custom pipelines for model training, fine-tuning, and deployment (LLMs, NLP, ML).

Cloud & Infrastructure :


- Deploy AI solutions using Azure Services (App Services, AI Foundry, Bot Services, AI Search, Containers).

- Set up end-to-end environments (Dev/Test/Prod) for ML/LLM/Agentic AI workloads.

- Implement serverless, containerized, and Kubernetes-based deployments for scalable AI applications.

- Use Infrastructure as Code (Terraform, ARM templates) for cloud provisioning and automation.

Data Engineering & Pipelines :


- Build ETL/data processing workflows using Apache Airflow, Kafka, Azure Data Factory.

- Integrate SQL/NoSQL, Data Lakes, and Data Warehouses into AI-driven applications.

- Manage data pipelines ensuring real-time ingestion, storage, and transformation.

MLOps & CI/CD :


- Establish MLOps frameworks (Kubeflow, MLflow, TFX) for training, deployment, and monitoring of ML/LLM models.


- Implement CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins) for AI models and services.

- Automate testing, monitoring, and retraining cycles to ensure continuous model improvement.

Optimization & Cost Management :


- Monitor and optimize cloud resource utilization to ensure cost efficiency and scalability.


- Implement auto-scaling strategies for AI workloads.

- Fine-tune large-scale models for performance and efficiency (latency, throughput, GPU/TPU usage).

Security & Compliance :


- Apply cloud security best practices (IAM, firewalls, VPCs, encryption).


- Ensure data privacy, secure access, and regulatory compliance in AI applications.

Collaboration & Delivery :


- Work in Agile environments (Scrum/Kanban) with cross-functional teams.


- Translate business needs into scalable Gen-AI solutions.

- Communicate complex AI concepts to both technical and non-technical stakeholders.

Technical Skills & Requirements :


Programming & AI Development :


- Strong C# and .NET experience (Mandatory).


- Hands-on with Semantic Kernel for AI orchestration.

- Expertise in LLM & Gen AI development.

- Familiarity with Agentic AI frameworks and autonomous agents.

Cloud & Infrastructure :


- Proficiency in Azure AI services (App Services, AI Foundry, AI Search, Bot Services, Containers).


- Experience with Kubernetes, Docker, serverless architectures.


- IaC tools : Terraform, ARM templates.

AI/ML & Data Engineering :


- Strong experience in ML, NLP, and LLM development.


- Familiar with MLOps pipelines (Kubeflow, MLflow, TFX).


- Data pipeline tools : Apache Airflow, Kafka, Azure Data Factory.

- Databases : SQL, NoSQL, Data Lakes, Warehouses.

Deployment & Optimization :

- Experience with custom model training, fine-tuning, and inference optimization.

- Knowledge of GPU/TPU environments, distributed model training.

- Performance tuning & cost management for cloud-based AI workloads.

Security & Compliance :

- Deep understanding of cloud security frameworks, IAM, encryption.

- Best practices in secure AI architecture and data governance.

Other :

- Strong problem-solving and debugging skills.

- Excellent written and verbal communication skills.

- Ability to work in fast-paced, cross-functional teams.

Preferred Qualifications :


- Experience with local LLM deployments and custom fine-tuning.

- Exposure to open-source AI orchestration frameworks.

- Certifications in Azure AI, Cloud Security, or MLOps.

- Hands-on with AI product lifecycle management from POC Production.


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