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
- 4 -6 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
Generative AI & LLMs
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Hands-on experience developing LLM-powered applications using Amazon Bedrock or similar platforms
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Experience building or contributing to Retrieval-Augmented Generation (RAG) pipelines, including:
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Document ingestion and chunking
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Embedding generation
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Similarity search using vector databases
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Practical knowledge of prompt engineering, prompt tuning, and output evaluation
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Multi agent workflow deployment experience
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Understanding of common LLM failure modes such as hallucinations and grounding issues
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Ability to evaluate LLM responses for accuracy, relevance, and safety
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Experience on AI/ML and computer vision is preferred
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Experience on pre sales on AI such as RFP response , Solution Architecture design , BOQ ( Hardwares and Softwares ) is required
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Experience on product and solutions is preferred.
Agentic AI (Growing Expertise)
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Exposure to Agentic AI concepts and frameworks such as AgentCore
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Experience implementing:
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Simple Autonomous agents or workflows
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Multi-step reasoning with predefined tools
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Familiarity with tool-calling, agent orchestration, and workflow automation
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Understanding the importance of:
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Guardrails
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Human-in-the-loop mechanisms
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Logging and observability for agent behavior
Cloud Platform:
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Working knowledge of key AWS services, including:
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S3, Lambda, Redshift, IAM, S3, AWS WAF, Query handler , Lambda
Professional & Collaboration Skills
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Strong Python programming skills and experience working with APIs
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Ability to work effectively in cross-functional teams (product, engineering, analytics)
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Willingness to learn quickly in a fast-evolving AI landscape ( flexibility and learning attitude )
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Comfortable taking technical guidance and implementing feedback
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Clear communication of findings, limitations, and model behavior to non-technical stakeholders
Nice to Have
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Initial exposure to AI governance, compliance, or ethical AI practices
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Experience with monitoring LLM outputs and basic evaluation frameworks
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Certifications in AWS Bedrock Gen AI Developer Professiona, Machine Learning, or Data Science
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Prior experience in enterprise or cloud-native environments
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