Senior AI Engineer who will lead the design, development, and deployment of advanced GenAI and LLM-powered solutions across cloud platforms. This role requires deep expertise in modern AI architectures, hands-on experience with large-scale model development, and the ability to build secure, scalable, cloud-native systems. Qualified professional will collaborate closely with engineering, data, and product teams to deliver high-impact AI capabilities that accelerate innovation across the organization.
Key Responsibilities:- Architect and implement GenAI and LLM-based systems, including fine-tuning, evaluation, and optimization
- Build scalable pipelines for data processing, model training, inference, and continuous improvement
- Deploy and manage AI workloads across AWS, Azure, or GCP using cloud-native services
- Integrate embeddings, vector search, and RAG pipelines into production environments
- Optimize GPU/accelerator utilization for distributed training and high-performance inference
- Develop automation for CI/CD, MLOps, observability, and model lifecycle management
- Ensure cloud security, compliance, and cost-efficient resource allocation
- Evaluate emerging AI frameworks, tools, and cloud services to drive innovation
- Partner with cross-functional teams to translate business needs into technical solutions
Requirements- 5-8+ years of experience in AI/ML engineering or cloud-based AI development
- Strong proficiency with Python and AI/ML frameworks (PyTorch, TensorFlow, JAX)
- Hands-on experience with LLMs, transformers, embeddings, and fine-tuning techniques
- Expertise with cloud platforms (AWS, Azure, or GCP) and services supporting AI workloads
- Experience with vector databases (Pinecone, Weaviate, FAISS) and RAG architectures
- Strong understanding of MLOps, CI/CD, containers, and orchestration (Docker, Kubernetes)
- Familiarity with GPU optimization, distributed compute, and model performance tuning
Preferred Skills:- Experience building GenAI-Powered applications and automation systems
- Knowledge of data engineering, ETL pipelines, and feature stores
- Familiarity with observability tools (Prometheus, Grafana, CloudWatch)
- Understanding of cloud security best practices and zero-trust principles
- Background in real-time inference and scalable microservices
BenefitsWhat We Offer:- High-impact role shaping the future of GenAI and cloud-native AI systems
- Opportunity to work with cutting-edge LLMs, cloud platforms, and emerging AI technologies
- Collaborative, innovative, and growth-driven environment
How to ApplyFor applications and inquiries, please email our Talent Team at
