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 overallexperience 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 solutions—from PoC to production—ensuring 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

Originally posted on Himalayas