About the role
- 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
- 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.
- 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
- Working knowledge of key AWS services, including:
- S3, Lambda, Redshift, IAM, S3, AWS WAF, Query handler , Lambda
- 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
- 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