AI Platform Engineer

• We are looking for an experienced AI Engineer with 4-8 years of experience in Machine Learning, Artificial Intelligence, and Generative AI.
• The ideal candidate will design, develop, and deploy scalable AI solutions across traditional machine learning and GenAI use cases.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Engineering, or related field.
• 8-10 years of experience in AI/ML or Data Science roles.
• Strong Python programming and AWS experience.

Key Responsibilities

• Build end-to-end ML solutions for classification, regression, recommendation, forecasting, clustering, anomaly detection, and optimization problems.
• Perform feature engineering, model experimentation, hyperparameter tuning, and model evaluation.
• Design and execute A/B testing and model validation strategies.
• Develop explainable and auditable ML models for business-critical applications.
• Monitor model performance and support retraining initiatives.
• Design and develop LLM-powered applications.
• Build RAG systems using vector databases and enterprise knowledge repositories.
• Develop AI copilots, intelligent assistants, and agentic workflows.
• Implement prompt engineering, prompt optimization, evaluation frameworks, and guardrails.
• Develop production-grade AI services, APIs, SDKs, and microservices.
• Design scalable REST APIs and event-driven architectures.
• Apply design patterns, SOLID principles, and clean coding standards.
• Work with Docker, EKS, SNS, SQS, and other AWS services.

Must-Have Skills

Python

• Strong hands-on experience with Python for developing production-grade AI and machine learning applications.
• Ability to write clean, maintainable, and reusable code following software engineering best practices.
• Experience developing APIs, automation frameworks, and AI services using Python.

SQL & Data Analysis

• Strong proficiency in SQL for data extraction, transformation, and analysis.
• Experience working with large-scale structured and semi-structured datasets.
• Ability to perform exploratory data analysis and derive business insights from data.

Machine Learning

• Strong expertise in machine learning algorithms and techniques including:
• Classification
• Regression
• Clustering
• Recommendation Systems
• Forecasting
• Anomaly Detection
• Hands-on experience with:
• Scikit-Learn
• XGBoost
• LightGBM
• CatBoost
• Deep understanding of:
• Feature Engineering
• Model Evaluation
• Hyperparameter Tuning
• Cross Validation
• Explainable AI

Deep Learning & NLP

• Practical experience developing NLP solutions using TensorFlow or PyTorch.
• Understanding of transformers, embeddings, and modern NLP techniques.
• Experience with text classification, semantic search, summarization, information extraction, and conversational AI use cases.

Generative AI

• Hands-on experience building enterprise-grade GenAI applications.
• Strong understanding of:
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Agentic AI Workflows
• Structured Output Generation
• Evaluation Frameworks
• Experience using frameworks such as:
• LangChain
• LangGraph

API & Software Engineering

• Experience designing and developing RESTful APIs and microservices.
• Strong understanding of design patterns, object-oriented programming, and SOLID principles.
• Experience creating reusable AI components, SDKs, and shared libraries.

AWS Cloud Technologies

• Working knowledge of AWS services commonly used for AI applications including:
• Amazon EKS
• SNS
• SQS
• Lambda
• S3
• API Gateway
• Ability to build scalable, cloud-native AI solutions.

Containerization

• Experience with Docker for packaging and deploying AI applications.
• Understanding of container-based application development and deployment.

Version Control

• Strong experience with Git and collaborative development workflows including code reviews, branching strategies, and release management.

Good-to-Have Skills

Apache Spark

• Experience processing large-scale datasets using Spark.
• Understanding of distributed data processing and big data workloads.

AI Agent Frameworks

• Experience with CrewAI or similar multi-agent frameworks.
• Understanding of agent orchestration, tool usage, memory management, and autonomous workflows.

Vector Databases

• Experience working with one or more of:
• OpenSearch
• pgvector
• Knowledge of embeddings, vector search, and semantic retrieval techniques.

Knowledge Graphs & GraphRAG

• Understanding of knowledge graph concepts and graph-based retrieval techniques.
• Exposure to GraphRAG architectures for improving reasoning and explainability.

Event-Driven Architecture

• Understanding of event-driven design patterns.
• Experience integrating SNS, SQS, Kafka, or similar messaging technologies into AI solutions.

Location

This position can be based in any of the following locations

Chennai

Current Guardian Colleagues: Please apply through the internal Jobs Hub in Workday