Job Description

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

• Optional skills Machine Learning and Neural networks
• 12-18 years of professional experience in 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 translate business and product requirements into data-driven solutions
• Strong Architecture Experience

Generative AI & LLMs & AI/ML

• Hands-on experience developing LLM-powered applications using Amazon 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 of prompt engineering, prompt tuning, and output evaluation
• Understanding of common LLM failure modes such as hallucinations and grounding issues
• Ability to evaluate LLM responses for accuracy, relevance, and safety
• AI/ML model actual Experience in model building
• Solution Architecture and Presales / GTM experience on AI/ML/LLM/Agentic AI

Agentic AI (Growing Expertise)

• Exposure to Agentic AI concepts and frameworks such as AgentCore
• Experience implementing:
  • Simple Autonomous agents or workflows
  • Multi-step reasoning with predefined tools
• Familiarity with tool-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 key AWS services, including: S3, Lambda, Redshift, IAM, S3, AWS WAF, Query handler, Lambda

Professional & Collaboration Skills

• Team mentoring and Solution Governance
• 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, Azure and GCP Machine Learning, or Data Science
• TOGAF Certification