Machine Learning Architect

Job Summary We are looking for a highly skilled Technical Architect with expertise in AWS, Generative AI, AI/ML, and scalable production-level architectures. The ideal candidate should have experience handling multiple clients, leading technical teams, and designing end-to-end cloud-based AI solutions with an overall experience of 9-12 years. This role involves architecting AI/ML/GenAI-driven applications, ensuring best practices in cloud deployment, security, and scalability while collaborating with cross-functional teams. Key Responsibilities Technical Leadership & Architecture Design and implement scalable, secure, and high-performance architectures on AWS for AI/ML applications. Architect multi-tenant, enterprise-grade AI/ML solutions using AWS services like SageMaker, Bedrock, Lambda, API Gateway, DynamoDB, ECS, S3, OpenSearch, and Step Functions. Lead full lifecycle development of AI/ML/GenAI solutionsfrom PoC to productionensuring reliability and performance. Define and implement best practices for MLOps, DataOps, and DevOps on AWS. AI/ML & Generative AI Expertise Design Conversational AI, RAG (Retrieval-Augmented Generation), and Generative AI architectures using models like Claude (Anthropic), Mistral, Llama, and Titan. Optimize LLM inference pipelines, embeddings, vector search, and hybrid retrieval strategies for AI-based applications. Drive ML model training, deployment, and monitoring using AWS SageMaker and AI/ML pipelines. Cloud & Infrastructure Management Architect event-driven, serverless, and microservices architectures for AI/ML applications. Ensure high availability, disaster recovery, and cost optimization in cloud deployments. Implement IAM, VPC, security best practices, and compliance. Team & Client Engagement Lead and mentor a team of ML engineers, Python Developer and Cloud Engineers. Collaborate with business stakeholders, product teams, and multiple clients to define requirements and deliver AI/ML/GenAI-driven solutions. Conduct technical workshops, training sessions, and knowledge-sharing initiatives. Multi-Client & Business Strategy Manage multiple client engagements, delivering AI/ML/GenAI solutions tailored to their business needs. Define AI/ML/GenAI roadmaps, proof-of-concept strategies, and go-to-market AI solutions. Stay updated on cutting-edge AI advancements and drive innovation in AI/ML offerings. Key Skills & Technologies Cloud & DevOps AWS Services: Bedrock, SageMaker, Lambda, API Gateway, DynamoDB, S3, ECS, Fargate, OpenSearch, RDS MLOps: SageMaker Pipelines, CI/CD (CodePipeline, GitHub Actions, Terraform, CDK) Security: IAM, VPC, CloudTrail, GuardDuty, KMS, Cognito AI/ML & GenAI LLMs & Generative AI: Bedrock (Claude, Mistral, Titan), OpenAI, Llama ML Frameworks: TensorFlow, PyTorch, LangChain, Hugging Face Vector DBs: OpenSearch, Pinecone, FAISS RAG Pipelines, Prompt Engineering, Fine-tuning Software Architecture & Scalability Serverless & Microservices Architecture API Design & GraphQL Event-Driven Systems (SNS, SQS, EventBridge, Step Functions) Performance Optimization & Auto Scaling