Generative AI / ML Engineer

Job Description –

Role Summary

We are seeking a Generative AI / ML Engineer to design, build, and deploy intelligent AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic workflows, and edge computing. You will work hands-on with cloud-native AI services, LLMOps pipelines, and enterprise-grade deployment patterns to solve business problems.

Key Responsibilities

• Design, develop, and fine-tune LLM-powered applications for enterprise use cases.
• Experience in evaluating LLM applications and developing observability frameworks
• Implement RAG pipelines using vector databases, embeddings, and optimized retrieval strategies.
• Build agentic AI workflows with multi-step reasoning, tool calling, and integration with APIs.
• Integrate GenAI solutions into multi-cloud or hybrid cloud environments (AWS, Azure, GCP).
• Develop and optimize edge AI deployments for low-latency use cases.
• Create data strategy, ingestion, transformation, enrichment, validations, quality checks via pipelines for AI ingestion, preprocessing, and governance.
• Implement AI safety, bias mitigation, and compliance measures.
• Work closely with LLMOps teams to enable continuous integration & deployment of AI models.
• Write well-documented, production-ready code in Python, Node.js, Rust .
• Benchmark and evaluate model performance , latency, and cost-efficiency.

Required Skills

Preferred Skills

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Skills Required

Microservices, Tensorflow, Security, Pytorch, Docker, Python, Aws, Rust, Apis, Node.js, Gcp, Data Privacy, Azure, Kubernetes