Artificial Intelligence Engineer
Artificial Intelligence Engineer
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Job Description
- AI Engineer Role Summary: Implement and operationalize AI/ML and GenAI solutions to drive SDLC automation and efficiency. Key Responsibilities:
- Develop and deploy AI/ML and GenAI solutions (LLMs, copilots, agents)
- Build automation use cases across coding, testing, documentation, and support
- Implement RAG pipelines, prompt engineering, and model orchestration
- Integrate AI solutions into SDLC tools and enterprise platforms
- Monitor model performance, accuracy, and adoption metrics
- Collaborate with architects and product teams to scale AI solutions Skills & Experience:
- 4–8 years in AI/ML or software engineering with AI exposure
- Hands-on experience with LLMs, prompt engineering, and RAG pipelines
- Proficiency in Python and AI frameworks (TensorFlow, PyTorch, LangChain, etc.)
- Experience building AI-powered applications, copilots, or automation tools
- Familiarity with API integration and microservices-based architectures
- Experience deploying models using MLOps tools and cloud platforms
- Understanding of model evaluation, monitoring, and performance tuning
- Strong problem-solving skills and ability to work in experimental environments
More Info
Key Skills
LangChain
LLMs
cloud platforms
microservices-based architectures
prompt engineering
model evaluation
MLOps tools
RAG pipelines
AI frameworks
About Company
Skills:
Power Platform, Azure Integration Services, Azure AI Services, Custom Python Development, AI ML Solution Development, API Integration and Automation, Copilot Studio
Skills:
PostgreSQL, Docker, Python, Azure DevOps, Git, Rest Apis, Anthropic Claude, Vector search, Azure OpenAI, LangGraph, GitHub Actions, AI-assisted development tools, Agentic workflows, Evaluation, Generative AI, Asynchronous processing, LLMs, Microsoft Foundry, Azure AI stack, Claude Code, Guardrails, Semantic Kernel, GitHub Copilot, Intelligent document processing, CI/CD, Microsoft Agent Framework, AI observability, OpenAI, Prompt design, Structured outputs
Skills:
containerization , Test-Driven Development (TDD), Java, Angular, React, Gcp, Docker, Azure, Python, AWS, Rabbitmq, Kafka, Redis, REST API lifecycle management, LLM API integration, Prompt engineering, CI/CD pipelines, Model fine-tuning, ML/LLM-driven development, Microservices architecture
Skills:
Ml, Apis, Data Architecture, Gcp, Azure, Python, AWS, LLM integration, Ai, prompt engineering, performance optimisation, model evaluation, scalable backend systems
Interesting Job Opportunity: Carelon - Artificial Intelligence Engineer - Python/LLMcarelon global solutions india
Skills:
Python, Tensorflow, Numpy, Pandas, AWS, Pytorch, Cloudformation, FastAPI, Kubernetes, Azure, Terraform, Gcp, Jenkins, Git, Spark, vLLM, GitHub Actions, MLflow, scikit-learn, Hugging Face Transformers, LangChain, TorchServe, TF Serving