Seeking an experienced AWS AI Data Engineer to design, build, and optimize scalable data and AI/ML solutions on AWS Cloud. The ideal candidate should possess strong expertise in modern data engineering, cloud-native architecture, machine learning data pipelines, and Generative AI solutions. The role involves developing robust data platforms, enabling AI workloads, and collaborating with data scientists, ML engineers, and business stakeholders to deliver impactful analytics and AI-driven solutions.
Design, develop data ingestion solutions from APIs, databases, and maintain scalable ETL/ELT pipelines on AWS.
Design, develop, and deploy Generative AI applications using Amazon Bedrock, SageMaker, and foundation models.
Build and implement Retrieval-Augmented Generation (RAG) solutions leveraging vector databases and enterprise knowledge repositories.
Enable AI/ML and Generative AI workloads through robust data pipelines.
Integrate Large Language Models (LLMs) with enterprise systems, APIs, and business workflows.
Design and optimize prompts, evaluate model performance, and improve response quality through prompt engineering techniques.
Implement AI guardrails, content filtering, and responsible AI practices to ensure safe and compliant GenAI deployments.
Monitor GenAI application performance, model usage, latency, and costs while ensuring scalability and reliability.
Implement and ensure data quality, governance, security, scalability, and cost-effective AWS data platforms.
Collaborate with Data Scientists, ML Engineers, and business stakeholders.
Develop conversational AI solutions, enterprise copilots, intelligent search, and knowledge-management applications.
Document technical solutions and support Agile delivery practices. ##LI-DNI
Strong experience with AWS Services: S3, Glue, Lambda, Redshift, DynamoDB, IAM, Step Functions, API Gateway, EC2, ECS/EKS.
Proficiency in Python, PySpark and SQL.
Hands-on experience with Amazon SageMaker and/or Amazon Bedrock, OpenSearch, Generative AI, RAG, Vector Databases, Prompt Engineering and LLM orchestration platforms.
Experience implementing enterprise scale RAG architecture, embeddings, and vector databases (OpenSearch, pgvector, Pinecone, Chroma, etc.).
Experience building and deploying scalable, secure, and production-grade GenAI and Agentic AI applications on AWS.
Strong understanding of Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, Multi-Agent Systems, and Conversational AI solutions.
Experience building enterprise AI copilots, chatbots, document intelligence, or knowledge assistant solutions.
Strong understanding of REST APIs, Microservices, CI/CD pipelines, Git, Docker, and cloud-native development practices.
Ability to work closely with business stakeholders and cross-functional teams to identify use cases and deliver AI-driven solutions.
Excellent analytical, problem-solving, and communication skills with a passion for innovation and emerging AI technologies.
Experience with Data Lakes, ETL/ELT, Data Warehousing, and Data Modeling.
Working experience with Terraform/CloudFormation, Git, CI/CD, and Docker.
Exposure to LLMOps, model evaluation, prompt optimization, monitoring, governance, and Responsible AI practices.
AWS Certifications (Developer Associate, Solutions Architect, Data Engineer, AI Practitioner) are a plus.
Location: Hyderabad
Designing better ways to work through cutting-edge products, premium services and exceptional experiences that enable people to reach their full potential. HR, Talent, Time Management, Benefits and Payroll. Informed by data and designed for people.
