HCF - AI Engineer

Core Responsibilities

• Design, develop, and deploy generative AI applications and systems (eg, intelligent document processing, conversational agents, knowledge retrieval systems)
• Work with data scientists and engineers to source, clean, and prepare datasets to build and optimize RAG (Retrieval-Augmented Generation) pipelines, multi-agent workflows, conversational interfaces) through API integration with LLMs (provided by OpenAI, Anthropic, Google), open-source models (eg Hugging Face/Lllama), and orchestration frameworks (LangChain, LangGraph, LlamaIndex).
• Integrate AI solutions into applications-build APIs, front-ends, and other endpoints for model interaction.
• Test, evaluate, and validate generative AI outputs for quality, safety, and fairness by using evaluation frameworks for LLM applications (accuracy, hallucination, recall).
• Implement prompt optimization strategies for cost and quality.
• Design conversation management and memory systems
• Build guardrails and safety layers for production LLM applications
• Document solutions, experiments, and code to ensure best practices and reproducibility.
• Collaborate closely with business and technical teams to align AI solutions with user and project needs.

Mandatory Skills

• Lead the design, implementation, and optimization of advanced/end-to-end generative architectures, including RAG, agents, and guardrails.
• Design evaluation strategies for complex LLM systems.
• Lead implementation of multi-agent orchestration systems.
• Design cost optimization strategies across LLM providers.
• Evaluate third-party models, frameworks, and open-source tools for adoption.
• Guide teams in responsible AI practices (eg, explainability, fairness).
• Engage with non-technical stakeholders to clarify complex AI concepts and solution value.
• Lead code reviews, establish coding standards, and mentor less experienced team members.

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