Key Responsibilities

- Strategic Advisory: Lead discovery workshops to identify high-value GenAI use cases (e.g., automated content generation, intelligent search, summarization, and data extraction).
- Solution Architecture: Design end-to-end AI architectures using Amazon Bedrock, including model selection (Claude, Titan, Llama, etc.), fine-tuning strategies, and RAG (Retrieval-Augmented Generation) pipelines.
- Technical Implementation: Build and deploy scalable AI applications utilizing AWS SageMaker, AWS Lambda, Amazon OpenSearch, and Vector Databases (Pinecone/pgvector).
- Prompt Engineering: Develop and optimize advanced prompt engineering frameworks to ensure high accuracy, safety, and relevance in model outputs.
- Governance & Ethics: Implement guardrails for responsible AI, ensuring data privacy, security, and regulatory compliance within the cloud setting.
- Client Engagement: Act as a trusted advisor to C-suite and technical leadership, translating complex technical roadmap items into clear business outcomes.

Mandatory Technical Skills




- AWS Core: Deep expertise in AWS cloud services (EC2, S3, IAM, VPC, Lambda, API Gateway).
- Generative AI (AWS Bedrock): Hands-on experience with Amazon Bedrock API, Knowledge Bases, Agents for Bedrock, and Guardrails.
- Frameworks & Libraries: Proficiency in LangChain, LlamaIndex, and Hugging Face libraries.
- Programming: Advanced Python development skills (Pandas, NumPy, PyTorch/TensorFlow).
- Data Engineering: Experience with Vector Databases and data orchestration tools relevant to LLMs.

- Preferred Qualifications

- Certifications: AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect – Professional.
- Consulting Experience: Proven track record in a top-tier consulting firm delivering large-scale digital transformations.
- Domain Knowledge: Experience in Financial Services, Retail, or Healthcare is a significant plus.

📌 AWS AI Engineer (Bengaluru)
🏢 Ariston Services
📍 Bengaluru