AWS and Gen AI Solution Architect

AWS and Gen AI Solution Architect

Location- PAN India

Experience-10+ Years

We are seeking a highly skilled Solution Architect AWS Cloud & AI/ML to design, architect, and implement advanced AI/ML and generative AI solutions on the AWS platform. The ideal candidate will have deep expertise in large-scale distributed systems, modern AI/ML architectures, LLMs, data engineering pipelines, and AWS-native services. This role involves partnering with cross-functional teams, understanding business challenges, and crafting endtoend scalable, secure, and costoptimized solutions.

Key Responsibilities

AI/ML & Generative AI Architecture

• Architect and deliver endtoend AI/ML solutions on AWS, covering data ingestion, training, inference, orchestration, monitoring, and governance.
• Design and integrate LLMbased and Generative AI solutions, including retrieval-augmented generation (RAG), prompt workflows, and production deployment strategies.
• Develop feature engineering strategies and scalable data pipelines to support ML training and real-time inference workloads.
• Lead technical discussions and provide guidance on AI/ML best practices, model lifecycle, optimization, MLOps, and model governance.

AWS Cloud Architecture

• Design highly scalable, secure, and cost-efficient architectures using:
• Amazon SageMaker (Training Jobs, Inference Endpoints, Pipelines, Feature Store, Model Registry)
• Amazon Bedrock (Foundation models, Generative AI orchestration, prompt management)
• AWS Lambda, ECS, EKS, EC2 for building and orchestrating distributed AI workloads.
• Architect and optimize data engineering platforms using:
• AWS Glue, Amazon Athena, Redshift, AWS Data Pipeline, S3, Kinesis, and related services.
• Build secure, production-grade API services for AI model inference using Amazon API Gateway and AWS compute services.

Solution Development & Technical Leadership

• Work with product, engineering, and business teams to convert requirements into scalable AWS-based AI solutions.
• Lead design reviews, create architecture diagrams, and document cloud patterns and reusable frameworks.
• Identify and manage risks related to scalability, performance, data quality, model drift, and security.
• Mentor engineering teams on AWS, AI/ML frameworks, and cloud-native development.

Required Skills & Experience

• 10+ years of experience in cloud architecture, with at least 5 years in AWS.
• Strong expertise in:
• Machine Learning, MLOps, and GenAI solution design.
• Amazon SageMaker (endtoend ML lifecycle).
• Amazon Bedrock and modern LLM architectures.
• Data engineering with Glue, Redshift, Athena, and pipeline orchestration.
• Experience containerizing and scaling AI workloads on Lambda/ECS/EKS.
• Strong coding experience in Python and familiarity with ML frameworks (TensorFlow, PyTorch, Scikitlearn).
• Deep understanding of security, networking, IAM, and compliance best practices for AI systems.
• Excellent communication, design thinking, and stakeholder management skills.

Preferred Qualifications

• AWS certifications (e.g., AWS Certified Solutions Architect Professional, Machine Learning Specialty).
• Experience with vector databases (e.g., Pinecone, OpenSearch, FAISS).
• Experience building RAG pipelines, multiagent orchestration frameworks, or custom LLM finetuning workflows.
• Familiarity with DevOps/MLOps tools: GitHub Actions, Airflow, Terraform, Docker, Kubernetes