SSenior AI Engineer
Description
Key Responsibilities :
- Design, develop, and deploy AI/ML and GenAI solutions in production environments.
- Build and optimize Agentic AI systems, LLM-powered applications, and recommendation engines.
- Develop scalable AI architectures, APIs, and model versioning frameworks.
- Implement distributed training, model evaluation, and performance optimization techniques.
- Collaborate with cross-functional teams to deliver high-performance AI solutions.
Required Skills :
- Strong programming expertise in Python, C++, Java, or Scala.
- Hands-on experience with LLMs, RAG, Agentic AI, PyTorch, and TensorFlow.
- Experience with LangChain, LangGraph, Hugging Face, and OpenCV.
- Familiarity with cloud platforms: Azure, AWS, or GCP.
- Knowledge of GPU Computing tools such as CUDA, Rapids, and NeMo.
- Experience building production-grade AI systems, Microservices, and APIs.
Good to Have :
- Neo4j, Knowledge Graphs
- Spark, Kafka, Redis, Elasticsearch
- Docker, Kubernetes, GitHub Actions, Terraform
- Experience with Real-Time AI/GenAI Systems and Responsible AI
Preferred Qualifications :
- Experience in Agentic AI, Reasoning Systems, Digital Twins, or Decision Intelligence.
- Strong communication and stakeholder management skills.
- Ability to thrive in a fast-paced, innovation-driven environment
Skills
- Agentic AI
- AI
- API
- AWS
- Azure
- Cloud
- C++
- CUDA
- Distributed Training
- Docker
- Elasticsearch
- GCP
- Generative AI
- GitHub
- GitHub Actions
- GPU
- Hugging Face
- Java
- Kafka
- Kubernetes
- LangChain
- LangGraph
- LLM
- Machine Learning
- Microservices
- Model Evaluation
- Neo4j
- OpenCV
- Python
- PyTorch
- RAG
- Redis
- Scala
- Spark
- Stakeholder Management
- TensorFlow
- Terraform