Data Scientist

Job Description

AI Engineer

Education

• • Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field
  • Strong academic foundation in statistics, probability, and LLM and Agentic AI and AWS Bedrock Experience
  • Machine Learning and Neural networks required
  • 3-5 years of professional experiencein LLM, Agentic AI
  • All aspects of BEDROCK, use of security APIs from AWS, Dynamo DB, Experience in Claude LLMs
  • Experience working on end-to-end Bedrock workflows
  • Ability to translatebusiness and product requirements into data-driven solutions

Generative AI & LLMs

• • Hands-on experience developingLLM-powered applications usingAmazon Bedrock or similar platforms
  • Experience building or contributing to Retrieval-Augmented Generation (RAG) pipelines, including:
  • Document ingestion and chunking
  • Embedding generation
  • Similarity search using vector databases
  • Practical knowledge ofprompt engineering, prompt tuning, and output evaluation
  • Understanding of commonLLM failure modes such ashallucinations and grounding issues
  • Ability to evaluate LLM responses for accuracy, relevance, and safety

Agentic AI (Growing Expertise)

• • Exposure toAgentic AI concepts and frameworks such asAgentCore
  • Experience implementing:
  • SimpleAutonomous agents or workflows
  • Multi-step reasoning with predefined tools
  • Familiarity withtool-calling, agent orchestration, and workflow automation
  • Understanding the importance of:
  • Guardrails
  • Human-in-the-loop mechanisms
  • Logging and observability for agent behavior

Cloud Platform:

• • Working knowledge of keyAWS services, including:
  • S3, Lambda, Redshift, IAM, S3, AWS WAF, Query handler , Lambda
  • Preferred Knowledge on MS Azure and GCP

Professional & Collaboration Skills

• • Strong Python programming skills and experience working with APIs
  • Ability to work effectively in cross-functional teams (product, engineering, analytics)
  • Willingness to learn quickly in a fast-evolving AI landscape ( flexibility and learning attitude )
  • Comfortable taking technical guidance and implementing feedback
  • Clear communication of findings, limitations, and model behavior to non-technical stakeholders

Nice to Have

• • Initial exposure to AI governance, compliance, or ethical AI practices
  • Experience with monitoring LLM outputs and basic evaluation frameworks
  • Certifications in AWS Bedrock Gen AI Developer Professional, Machine Learning, or Data Science; Certified Claude AI Architect ( foundation)