- Company Name
- Leute Passen Technologies
- Job Title
- Senior LLM & AI Specialist
- Job Description
-
- **Job Title:** Senior LLM & AI Specialist
- **Role Summary:** Lead end‑to‑end design, development, deployment, and client delivery of large language model (LLM) solutions, including retrieval‑augmented generation, agent systems, and copilots. Own production pipelines, cloud architecture, and MLOps best practices while mentoring and scaling an AI delivery team and serving as the primary technical advisor to enterprise clients.
- **Expectations:** Within 12 months deliver multiple complete LLM projects that meet or exceed defined success metrics; establish the organization as a trusted AI advisor; create reusable frameworks and best‑practice patterns; assume clear leadership of a growing technical team.
- **Key Responsibilities:**
1. Architect and implement LLM systems (RAG, fine‑tuning, agents, copilots) from concept through production.
2. Design end‑to‑end AI pipelines: data ingestion, preprocessing, model evaluation, deployment, and monitoring.
3. Select, benchmark, and optimize commercial and open‑source LLMs (GPT, Claude, LLaMA) for performance, cost, and security.
4. Build scalable, secure, cloud‑native AI infrastructures on AWS, Azure, or GCP.
5. Act as the main technical liaison for enterprise clients; translate business needs into technical solutions.
6. Lead workshops, solution demos, and presentations for technical and executive stakeholders.
7. Own project timelines, risk mitigation, scope management, and delivery across multiple engagements.
8. Mentor and coach junior/mid‑level data scientists and ML engineers; participate in hiring and onboarding.
9. Define and enforce coding standards, documentation, model governance, and MLOps processes.
10. Continuously refine reusable patterns and operational frameworks to improve team efficiency and quality.
- **Required Skills:**
* Deep technical mastery of LLM architectures (RAG, fine‑tuning, inference optimization).
* Proficient in Python, PyTorch or TensorFlow.
* Strong prompt engineering and knowledge of retrieval‑augmented generation.
* Experience deploying and monitoring models on major cloud platforms (AWS, Azure, GCP).
* MLOps expertise: CI/CD, containerization (Docker/Kubernetes), model monitoring (MLflow, Weights & Biases).
* Client‑facing consulting, stakeholder management, and persuasive presentation skills.
* Leadership and team‑building capabilities.
* Understanding of AI governance, responsible AI, data privacy, and security standards.
- **Required Education & Certifications:**
* Bachelor’s or advanced degree in Computer Science, Engineering, Data Science, or related field.
* Minimum 6 years of professional experience in data science, machine learning, or AI engineering.
* Relevant cloud certification preferred (e.g., AWS Certified Machine Learning – Specialty, GCP Professional Data Engineer, Azure AI Engineer Associate).