AI & LLM Executive

Marham is seeking an AI & LLM Executive with 1 to 2 years of hands-on experience in Artificial Intelligence, Large Language Models (LLMs), and AI-driven application development. The successful candidate will play a crucial role in building, integrating, and optimizing AI solutions aimed at enhancing operational efficiency, automating repetitive tasks, and improving healthcare experiences for both doctors and patients. This role requires a proactive individual who can translate complex business challenges into practical AI applications while collaborating closely with cross-functional teams.

Key Responsibilities
- AI Solution Development: Design and implement AI-powered solutions using LLMs to address real-world business challenges and boost operational efficiency.
- LLM Integration: Integrate models such as OpenAI, Gemini, Claude, or open-source LLMs into internal tools and customer-facing platforms.
- Prompt Engineering: Develop, test, and refine prompts to enhance the accuracy, relevance, consistency, and reliability of AI responses.
- Workflow Automation: Identify repetitive processes and create AI-driven automations to reduce manual effort and improve turnaround times.
- API Development & Integration: Utilize REST APIs, Python, and third-party services to embed AI capabilities into existing systems.
- RAG & Knowledge Systems: Support the creation of Retrieval-Augmented Generation (RAG) solutions using company knowledge bases, embeddings, and vector databases.
- Testing & Evaluation: Assess AI outputs for accuracy, hallucinations, response quality, latency, and cost, implementing improvements as needed.
- Data Processing: Prepare, clean, and structure data and documents for AI applications while ensuring data privacy and security.
- Cross-functional Collaboration: Partner with Product, Engineering, and Operations teams to identify AI opportunities that deliver measurable business value.
- Documentation: Maintain comprehensive documentation of AI workflows, integrations, testing outcomes, and implementation guidelines.

Required Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
- 1 to 2 years of practical experience in AI, LLM applications, automation, or a similar technical role.
- Proficiency in Python and experience working with APIs.
- Hands-on experience with LLM APIs such as OpenAI, Gemini, or Claude.
- Solid understanding of prompt engineering, embeddings, tokenization, and context windows.
- Basic knowledge of RAG pipelines, vector databases, and semantic search techniques.
- Familiarity with Git, JSON, REST APIs, and debugging tools.
- Strong analytical and problem-solving abilities.
- Ability to learn quickly, experiment with emerging technologies, and convert business needs into effective AI solutions.

Preferred Qualifications
- Experience with frameworks like LangChain, LlamaIndex, or LangGraph.
- 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 methods, guardrails, and responsible AI principles.
- Experience deploying AI applications using cloud platforms or Docker.

Success Metrics
Success in this role will be measured by tangible business outcomes, including reducing manual effort in at least one key workflow within the first 90 days, improving AI output accuracy and reliability, demonstrating measurable efficiency gains within six months, optimizing model usage and costs without sacrificing quality, and delivering AI solutions on time with thorough documentation and measurable impact.

We are looking for a candidate who takes ownership, embraces experimentation, and prioritizes outcomes over simply using AI tools. The ideal professional will be comfortable working independently, collaborating across teams, and building practical AI solutions that address real-world problems.

Work Location: This position requires in-person attendance.