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