Senior AI Engineer
At a glance
Senior AI Engineering role at Fa Ewjt Saasfaprod1. Noida · full-time.
Pay not stated AI Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and launch machine learning and generative AI solutions using LLMs and current AI frameworks
- Fine-tune and optimize LLMs, shape prompts, and create retrieval-augmented generation workflows
- Run AI pipelines and generative AI applications in production on Azure or Google Cloud
- Develop agent-based AI systems, prepare data for training and evaluation, and connect models to enterprise software
- Protect PII and PHI, improve system performance and cost, and document models, experiments, and operations
What you bring
- A bachelor’s degree in engineering, computer science, AI/ML, data science or a related technical area
- At least ten years in software engineering, machine learning or AI engineering, including three years with generative AI and LLMs
- Strong Python skills and practical experience tuning, deploying and improving LLMs in production
- Experience with Linux, Azure or Google Cloud, MLOps pipelines, and compliant handling of sensitive information
Who this fits
This senior role suits an engineer who has taken generative AI and LLM systems into production and can work across data, software and business teams. The position is hybrid in Noida, India.
From the employer
We are seeking an experienced AI / Generative AI Engineer to design, develop, and deploy advanced AI-driven solutions leveraging large language models (LLMs) and modern Generative AI technologies. This role will focus on building scalable AI systems, deploying GenAI applications in production environments, and ensuring secure handling of sensitive data such as PII/PHI.
The ideal candidate will bring deep expertise in machine learning, generative AI model development, cloud-based AI infrastructure, and production deployment. The role requires strong collaboration with data scientists, software engineers, and business stakeholders to build reliable and responsible AI solutions that solve complex enterprise problems.
- Design, develop, and deploy Generative AI and machine learning solutions using large language models and modern AI frameworks.
- Implement LLM fine-tuning, prompt engineering, retrieval-augmented generation (RAG), and model optimization techniques.
- Deploy and manage AI/ML pipelines and GenAI applications in production environments using cloud platforms such as Azure or GCP.
- Build and maintain agentic AI systems leveraging modern orchestration and agent frameworks.
- Work with large datasets to build data pipelines and ensure effective model training and evaluation.
- Develop AI solutions using Python and modern ML libraries.
- Manage deployments and infrastructure in Linux-based environments.
- Ensure secure processing and governance of sensitive data, including PII and PHI, adhering to enterprise security and compliance standards.
- Optimize AI models and infrastructure for performance, scalability, reliability, and cost efficiency.
- Collaborate with cross-functional teams to integrate AI models into enterprise applications and production systems.
- Document model architectures, experiments, deployment pipelines, and operational processes.
- Stay current with emerging developments in Generative AI, LLMs, and AI engineering practices.
- Bachelor’s degree in Engineering, Computer Science, AI/ML, Data Science, or a related technical field.
- 10+ years of overall professional experience in software engineering, machine learning, or AI engineering.
- Minimum 3+ years of hands-on experience working with Generative AI technologies and LLMs.
- Strong programming experience in Python.
- Proven experience fine-tuning, deploying, and optimizing large language models.
- Experience deploying Generative AI solutions into production environments.
- Hands-on experience working with Linux-based systems.
- Experience with cloud platforms such as Microsoft Azure or Google Cloud Platform (GCP).
- Experience building ML pipelines and deploying AI models using modern MLOps practices.
- Experience handling and securing sensitive data such as PII and PHI in compliance with security and regulatory requirements.