Gen AI Engineer (SJ-IQ)
Gen AI Engineer (SJ-IQ)
SE-Mentor Solutions (P) Ltd6-8 Years
- Posted 19 hours ago
- Be among the first 10 applicants
Job Description
6+ years of experience building and delivering production-grade full-stack applications, AI products, and cloud-native services.
Design and develop end-to-end AI solutions using LLMs, RAG, agentic AI frameworks, and multimodal foundation models for text, audio, image, and video generation.
Build scalable AI applications using Python, TypeScript, REST APIs, microservices, and Azure cloud services.
Architect and optimize conversational AI, Digital AI Agents (DAX), GitHub + copilots, and task automation workflows leveraging Azure OpenAI and modern AI platforms.
Implement Vector Database and semantic retrieval solutions to power enterprise knowledge search, reasoning, and grounding capabilities.
Develop and operationalize LLMOps/MLOps pipelines including model deployment, evaluation, observability, prompt management, guardrails, and continuous monitoring.
Integrate speech-to-text, text-to-speech, audio intelligence, image generation, and video generation capabilities into AI-powered user experiences8 using LLM Models & API calls (Gemini, GPT 5 and higher, DALL-E-3.0) .
Build and deploy scalable workloads on Azure, Databricks, AKS/Kubernetes, Azure Data Lake Gen2, and event-driven architectures.
Establish CI/CD, automated testing, security, and governance standards for AI applications using GitHub and Azure DevOps.
Drive adoption of AI-assisted development, coding agents, and autonomous research systems across teams.
Key Technologies
Azure OpenAI
Design and develop end-to-end AI solutions using LLMs, RAG, agentic AI frameworks, and multimodal foundation models for text, audio, image, and video generation.
Build scalable AI applications using Python, TypeScript, REST APIs, microservices, and Azure cloud services.
Architect and optimize conversational AI, Digital AI Agents (DAX), GitHub + copilots, and task automation workflows leveraging Azure OpenAI and modern AI platforms.
Implement Vector Database and semantic retrieval solutions to power enterprise knowledge search, reasoning, and grounding capabilities.
Develop and operationalize LLMOps/MLOps pipelines including model deployment, evaluation, observability, prompt management, guardrails, and continuous monitoring.
Integrate speech-to-text, text-to-speech, audio intelligence, image generation, and video generation capabilities into AI-powered user experiences8 using LLM Models & API calls (Gemini, GPT 5 and higher, DALL-E-3.0) .
Build and deploy scalable workloads on Azure, Databricks, AKS/Kubernetes, Azure Data Lake Gen2, and event-driven architectures.
Establish CI/CD, automated testing, security, and governance standards for AI applications using GitHub and Azure DevOps.
Drive adoption of AI-assisted development, coding agents, and autonomous research systems across teams.
Key Technologies
Azure OpenAI
- GPT-4o / DAX Models
- RAG
- Agentic AI
- Vector DBs
- Databricks
- Python
- AKS
- Azure AI Speech
- Image/Video/Audio Generation APIs
- GitHub Copilot
- Azure DevOps
- LLMOps
More Info
Key Skills
LLMOps
Vector DBs
AKS
Azure OpenAI
Azure AI Speech
DAX Models
GitHub Copilot
Agentic AI
Image Video Audio Generation APIs
RAG
GPT-4
