AI Agent and LLM Engineer Role Overview
Welcome to the AI Agent and LLM Engineer Role page. You can use this role template
as is or customize it to fit your needs and environment.
- Category: Information & Technology > Application/Web Development
Summary
The AI Agent and LLM Engineer is a specialized AI engineering role focused on designing, building, fine-tuning, and deploying advanced large language model (LLM)-based agents and intelligent agentic systems that autonomously perform complex, multi-step tasks for enterprise clients. This engineer translates business use cases into production-grade AI agents capable of reasoning, tool use, memory management, planning, and human-in-the-loop interaction. Working within Wipro’s AI services and GenAI practice, the role combines deep expertise in LLMs, agent frameworks, prompt engineering, retrieval-augmented generation (RAG), and evaluation to deliver high-reliability, scalable, and secure AI solutions in regulated industries. The engineer collaborates closely with client architects, data teams, and product owners to ensure agents integrate seamlessly with enterprise systems, meet governance and compliance standards, and drive measurable business outcomes such as process automation, decision support, and customer experience enhancement.
Responsibilities
- Design and architect AI agents and multi-agent systems using LLMs to solve specific enterprise workflows (e.g., customer support, procurement automation, code generation, research synthesis).
- Implement advanced agent capabilities including reasoning chains, tool calling, memory (short-term/long-term), planning/re-planning, reflection, and error recovery.
- Develop and optimize retrieval-augmented generation (RAG) pipelines with vector databases and hybrid search for accurate, context-aware responses.
- Fine-tune, prompt-engineer, and evaluate LLMs (open-source and proprietary) to achieve target performance on domain-specific tasks.
- Integrate agents with enterprise systems via APIs, orchestration layers, and secure authentication mechanisms.
- Build evaluation frameworks (automated benchmarks, human-in-the-loop eval, A/B testing) to measure agent reliability, accuracy, safety, and cost-efficiency.
- Ensure compliance with data privacy (GDPR, CCPA, DPDP), AI ethics guidelines, bias mitigation, and hallucination controls.
- Collaborate with client stakeholders to define success metrics, conduct PoCs/pilots, and support production rollout and monitoring.
Qualifications and Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
- 5+ years of hands-on experience building production AI/ML systems, with at least 2–3 years specifically focused on LLMs, generative AI, or agentic systems.
- Proven track record shipping LLM-powered applications or agents in enterprise or client-facing environments (e.g., financial services, healthcare, telecom, or manufacturing).
- Experience with both open-source and proprietary LLMs in real-world deployments.
- Familiarity working in agile teams within IT services/consulting organizations.
Skills
Tech Experts
