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 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 Scali