AI Engineer (GenAI / Hyperscaler / Agentic AI)

We are seeking a skilled AI Engineer with strong experience in Generative AI, Hyperscaler AI services, and Agentic AI systems. The ideal candidate will have hands-on expertise in building LLM-based use cases, backend AI integrations, and deploying scalable AI solutions on AWS and Azure platforms.

Key Responsibilities

• Design and develop GenAI and Agentic AI solutions using modern LLM frameworks.
• Build and implement real-world use cases leveraging LLMs such as Anthropic Claude, Google Gemini, AWS Nova, and Meta Llama.
• Develop backend tools and services to support AI-driven applications.
• Work with AWS Bedrock and SageMaker for model deployment, orchestration, and optimization.
• Utilize Azure AI Foundry services for AI solution development on Azure.
• Implement Retrieval-Augmented Generation (RAG) pipelines using Vector Databases and embeddings.
• Perform fine-tuning and optimization of foundation models.
• Manage token usage, prompt engineering, and context optimization for LLM applications.
• Collaborate with cross-functional teams to translate business requirements into AI solutions.
• Ensure scalability, performance, and security of AI systems in production environments.

Required Skills

• 4+ years of software/AI engineering experience with at least 2 years in GenAI/LLM space.
• Strong hands-on experience with MCP, Agentic AI concepts, and LLM application development.
• Experience with AWS AI stack: Bedrock, SageMaker.
• Experience with Azure AI Foundry or equivalent Azure AI services.
• Practical exposure to LLMs: Anthropic Claude, Google Gemini, AWS Nova, Meta Llama.
• Solid understanding of Vector Databases, embeddings, token management, and RAG architectures.
• Experience in fine-tuning foundation models.
• Proficiency in Python and backend development.
• Familiarity with REST APIs, microservices, and cloud-native architectures.
• Good understanding of MLOps and CI/CD for AI workloads.
• Must possess an innovative mindset with a proactive problem-solving approach.

Preferred Qualifications

• Experience building production-grade GenAI applications.
• Knowledge of prompt engineering and evaluation frameworks.
• Exposure to multi-agent or autonomous AI systems.
• Experience with Kubernetes/Docker is a plus.
• Strong problem-solving and communication skills.