IN_Sr Associate_GEN / Agentic AI Engineer _D&A_Advisory_Gurgaon

Job Description & Summary 

A career within Data & Analytics Services will provide you with the opportunity to help our clients leverage transformation to enhance their customer experiences. 

*Responsibilities:  

  
Technical Skills:  
• Advanced proficiency in Python.  
• Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques  
• Experience with big data processing using Spark for large-scale data analytics  
• Version control and experiment tracking using Git and MLflow  
• Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing.  
• DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations.  
• LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as vLLM and FastAPI, model quantization techniques, and vector database management.  
• MLOps & Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like TorchServe or TF Serving, and automated model retraining.  
• Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems.  
• LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation services, and optimizing LLMs for performance and security.  
• General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face, TensorFlow, PyTorch), and experience with cloud platforms like AWS or GCP.  
• Experience in creating LLD for the provided architecture.  
• Experience working in microservices based architecture.  
  
Domain Expertise:  
• Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation  
• Expertise in feature engineering, embedding optimization, and dimensionality reduction  
• Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing  
• Experience with RAG systems, vector databases, and semantic search implementation  
• Proficiency in LLM optimization techniques including quantization and knowledge distillation  
• Understanding of MLOps practices for model deployment and monitoring  
Professional Competencies:  
• Strong analytical thinking with ability to solve complex ML challenges  
• Excellent communication skills for presenting technical findings to diverse audiences  
• Experience translating business requirements into data science solutions  
• Project management skills for coordinating ML experiments and deployments  
• Strong collaboration abilities for working with cross-functional teams  
• Dedication to staying current with latest ML research and best practices  
• Ability to mentor and share knowledge with team members  
  
 
(Python, FastAPI, Microservices, K8s, RAG, VectorDBs)  

*Mandatory skill sets  

• Develop and maintain microservice architecture and API management solutions using REST and gRPC for seamless deployment of AI solutions.  
• Collaborate with cross-functional teams, including data scientists and product managers, to acquire, process, and manage data for AI/ML model integration and optimization.  
• Design and implement robust, scalable, and enterprise-grade data pipelines to support state-of-the-art AI/ML models.  
• Debug, optimize, and enhance machine learning models, ensuring quality assurance and performance improvements.  
• Familiarity with tools like Terraform, CloudFormation, and Pulumi for efficient infrastructure management.  
• Create and manage CI/CD pipelines using Git-based platforms (e.g., GitHub Actions, Jenkins) to ensure streamlined development workflows.  
• Operate container orchestration platforms like Kubernetes, with advanced configurations and service mesh implementations, for scalable ML workload deployments.  
• Design and build scalable LLM inference architectures, employing GPU memory optimization techniques and model quantization for efficient deployment.  
• Engage in advanced prompt engineering and fine-tuning of large language models (LLMs), focusing on semantic retrieval and chatbot development.  
• Document model architectures, hyperparameter optimization experiments, and validation results using version control and experiment tracking tools like MLflow or DVC.  
• Research and implement cutting-edge LLM optimization techniques, such as quantization and knowledge distillation, ensuring efficient model performance and reduced computational costs.  
• Collaborate closely with stakeholders to develop innovative and effective natural language processing solutions, specializing in text classification, sentiment analysis, and topic modeling.  
• Design and execute rigorous A/B tests for machine learning models, analyzing results to drive strategic improvements and decisions.  
• Stay up-to-date with industry trends and advancements in AI technologies, integrating new methodologies and frameworks to continually enhance the AI engineering function.  
• Contribute to creating specialized AI solutions in healthcare, leveraging domain-specific knowledge for task adaptation and deployment.  
Enable Skills-Based Hiring No  

Preferred Skill Sets: 
GenAI / LLM Engineers  *Preferred skill sets  

Python, Machine learning , Deep learning  

Years of experience required  

5+ years 

Employment Type : Full Time, Permanent 

*Education Qualification   

Full time B. E