AI & LLM Executive

About the Role
Marham is looking for an AI & LLM Executive with 1–2 years of hands-on experience in Artificial Intelligence, Large Language Models (LLMs), and AI-powered application development. The ideal candidate will help build, integrate, and optimize AI solutions that improve operational efficiency, automate repetitive tasks, and enhance healthcare experiences for doctors and patients.
Key Responsibilities

• AI Solution Development: Build and implement AI-powered solutions using LLMs to solve real business problems and improve operational efficiency.
• LLM Integration: Integrate models such as OpenAI, Gemini, Claude, or open-source LLMs into internal tools and customer-facing applications.
• Prompt Engineering: Design, test, and optimize prompts to improve response accuracy, relevance, consistency, and reliability.
• Workflow Automation: Identify repetitive business processes and develop AI-driven automations that reduce manual effort and turnaround time.
• API Development & Integration: Work with REST APIs, Python, and third-party services to integrate AI capabilities into existing systems.
• RAG & Knowledge Systems: Assist in building Retrieval-Augmented Generation (RAG) solutions using company knowledge bases, embeddings, and vector databases.
• Testing & Evaluation: Evaluate AI outputs for accuracy, hallucinations, response quality, latency, and cost; implement improvements based on results.
• Data Processing: Prepare, clean, and structure data and documents for AI applications while maintaining data privacy and security.
• Cross-functional Collaboration: Work with Product, Engineering, and Operations teams to identify opportunities where AI can deliver measurable business value.
• Documentation: Maintain clear documentation of AI workflows, integrations, testing results, and implementation guidelines.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
• 1–2 years of hands-on experience in AI, LLM applications, automation, or a related technical role.
• Proficiency in Python and experience working with APIs.
• Practical experience with LLM APIs such as OpenAI, Gemini, or Claude.
• Understanding of prompt engineering, embeddings, tokenization, and context windows.
• Basic knowledge of RAG pipelines, vector databases, and semantic search.
• Familiarity with Git, JSON, REST APIs, and debugging.
• Strong analytical and problem-solving skills.
• Ability to learn quickly, experiment with new technologies, and translate business problems into practical solutions.

Preferred Qualifications

• Experience with LangChain, LlamaIndex, LangGraph, or similar frameworks.
• Familiarity with vector databases such as Pinecone, Qdrant, Chroma, or FAISS.
• Exposure to AI agents, tool calling, function calling, and workflow automation.
• Understanding of LLM evaluation, guardrails, and responsible AI practices.
• Experience deploying AI applications using cloud services or Docker.

Success Metrics
Success in this role will be measured by business outcomes, including:

• Automation Impact: Reduce manual effort in at least one prioritized business workflow within the first 90 days.
• Solution Quality: Improve the accuracy and reliability of AI outputs against agreed evaluation benchmarks.
• Efficiency: Demonstrate measurable improvements in turnaround time for selected workflows within the first six months.
• Cost Optimization: Monitor and optimize model usage, latency, and cost without compromising agreed quality standards.
• Delivery & Ownership: Deliver assigned AI solutions within agreed timelines, with documented testing and measurable results.

What We’re Looking For
We are looking for someone who takes ownership, experiments with new ideas, and focuses on outcomes rather than simply using AI tools. You should be comfortable learning independently, collaborating with different teams, and building practical AI solutions that solve real problems.

Work Location: In person