4 hours ago
Responsibilities
- Design and implement generative AI and AI-agent solutions for customer service and contact center scenarios.
- Develop prompts, system instructions, context strategies, tool-calling patterns, and multi-step agent workflows.
- Design and implement RAG solutions using enterprise knowledge sources.
- Integrate AI agents with APIs, databases, business applications, knowledge repositories, and external tools.
- Select and evaluate foundation models based on quality, latency, cost, and operational constraints.
- Implement grounding, hallucination mitigation, guardrails, content controls, PII protection, and safety mechanisms.
- Design conversational context, session state, memory, fallback, and human-escalation patterns.
- Define observability, tracing, quality metrics, and operational monitoring for AI-agent behavior.
- Optimize prompts, retrieval strategies, model configuration, token consumption, latency, and cost.
- Create evaluation datasets, regression suites, and release quality thresholds with AI Output Testing Engineers.
- Translate Responsible AI and governance requirements into technical controls.
- Participate in architecture reviews, code reviews, technical documentation, and production support.
Requirements
- 10+ years of relevant technical experience, including delivery of Generative AI or LLM-based applications in enterprise environments.
- At least 2 years of experience with Amazon Bedrock.
- Strong software engineering experience, preferably using Python and/or TypeScript.
- Practical experience with prompt engineering, context engineering, RAG, embeddings, vector search, semantic search, and tool or function calling.
- Experience designing or implementing AI agents and multi-step agentic workflows.
- Experience integrating LLM solutions with REST APIs, enterprise applications, databases, and knowledge sources.
- Strong understanding of hallucination mitigation, grounding, prompt injection, jailbreak prevention, content filtering, and context-window management.
- Experience evaluating model and agent outputs through automated and human evaluation approaches.
- Experience with Git, automated testing, and production software delivery practices.
- Ability to communicate complex AI concepts to technical and business stakeholders.
- Professional proficiency in English.
- Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field.
- Experience with Amazon Connect, Amazon Q in Connect, agent-assist, knowledge-assistance, customer-support AI, or frameworks such as LangChain, LangGraph, LlamaIndex, and Semantic Kernel is preferred.
Benefits
- 100% remote work for candidates located in LATAM.
- One-year contract with potential for extension.
- Candidates must use a personal laptop and permit company security software and device-management tools to be installed for the engagement.
Tech Stack
Categories
About NTT DATA
NTT DATA is a Tokyo‑headquartered, publicly traded IT services firm within the NTT Group. It provides consulting, application development, system integration, cloud and enterprise application services, and managed/outsourcing services for large enterprises and public-sector organizations. The company operates in more than 50 countries and is listed on the Tokyo Stock Exchange.