Educational Requirements

Bachelor of Engineering, BTech, BSc, BCA, MTech, MSc, MCA

Service Line

Data Analytics Unit

Responsibilities

AWS Bedrock Generative AI: Design and build GenAI solutions using AWS Bedrock and foundation models (FM) such as Amazon Titan, Anthropic Claude, etc.
LLM-based applications: Implement LLM-based applications like chatbots, summarization engines, recommendation systems, and document intelligence
Prompt engineering, fine-tuning, and model evaluation: Apply advanced prompt engineering, fine-tuning, and model evaluation techniques
RAG pipelines: Design RAG (Retrieval-Augmented Generation) pipelines and integrate vector databases
Python Development: Develop scalable backend systems using Python (FastAPI, Flask, Django)
APIs and microservices: Build APIs and microservices to integrate AI/ML services into business applications
Data preprocessing, automation, and orchestration: Write efficient scripts for data preprocessing, automation, and orchestration
AWS Cloud Architecture: Design cloud-native solutions using AWS services (Lambda, API Gateway, S3, EC2, IAM, CloudWatch, Step Functions)
Security, scalability, and availability: Architect secure, scalable, and highly available systems
Cost optimization and performance: Optimize cloud cost and performance
Data privacy and compliance: Ensure data privacy and compliance for AI workloads
Data AI Integration: Work with structured unstructured datasets for AI applications
Data pipelines: Build pipelines to integrate external data sources with LLMs
Vector search and semantic capabilities: Implement vector search, embeddings, and semantic search capabilities
Collaboration Leadership: Collaborate with data scientists, ML engineers, product teams, and business stakeholders
Leadership in design discussions: Lead design discussions and provide technical guidance to junior developers
Agile/Scrum: Participate in Agile/Scrum development cycles

Additional Responsibilities

Preferred Skills: Experience with LangChain, LlamaIndex, or similar frameworks
Knowledge of vector databases (FAISS, Pinecone, Weaviate, OpenSearch)
Exposure to Docker, Kubernetes, and containerization
Understanding of ML lifecycle, MLOps, and model deployment
Experience in big data or data engineering tools (Glue, Redshift, Spark)

Technical and Professional Requirements

Primary skills: Technology- >Geographical Information System- >Spatial Databases- >SQL Server,Technology- >OpenSystem- >Python - OpenSystem

Preferred Skills

Technology- >OpenSystem- >Python - OpenSystem- >Python
Technology- >AI-Generative AI- >Generative AI - Basic- >closed models (aws bedrock)

AWS Bedrock Developer+Python

Job Description

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