- Company Name
- Wissen Technology
- Job Title
- Lead Gen AI
- Job Description
-
**Job title**: Lead Gen AI
**Role Summary**: Senior architect and technical lead responsible for designing, building, and operationalizing enterprise‑grade generative AI solutions. Drives end‑to‑end implementation, from architecture to production deployment, ensuring scalable, secure, and high‑performance AI systems.
**Expectations**: Deliver fully functional GenAI products, mentor technical teams, set architectural best practices, and collaborate with cross‑functional stakeholders to align AI initiatives with business objectives.
**Key Responsibilities**
1. Lead the design and implementation of scalable GenAI architectures, integrating LLMs, vector databases, RAG pipelines, and prompt‑engineering frameworks.
2. Build production‑ready AI applications using LangChain, LlamaIndex, Hugging Face, OpenAI, Azure OpenAI, or equivalent; develop APIs, microservices, and backend components.
3. Conduct proofs‑of‑concept, prototypes, performance benchmarking, and continuous optimization of models (fine‑tuning, evaluation, prompt tuning).
4. Oversee end‑to‑end solution delivery, including data pipelines, embeddings, model lifecycle management, and MLOps practices on cloud platforms (Azure, AWS, GCP).
5. Troubleshoot model performance, data quality, latency, and integration issues; provide technical guidance to developers, data scientists, and engineering teams.
6. Define reference architectures, reusable components, and best practices for GenAI adoption across the organization.
7. Partner with product, engineering, data, and business stakeholders to identify use cases, develop roadmaps, and communicate architectural decisions and risks to senior leadership.
8. Mentor team members, contribute to building internal AI capability, and stay current with emerging GenAI technologies and research.
**Required Skills**
- 7+ years in software engineering, AI/ML development, or related technical roles.
- Expertise in AI/ML architecture, solution design, and cloud‑native systems.
- Hands‑on experience with LLMs, GenAI frameworks, vector databases, and RAG architectures.
- Proficiency in Python, API development, and modern cloud platforms (Azure, AWS, GCP).
- Strong understanding of data pipelines, embeddings, model lifecycle, and MLOps.
- Excellent analytical, debugging, and problem‑solving skills.
- Ability to lead technical discussions and drive end‑to‑end solution delivery.
**Preferred Qualifications**
- Experience with fine‑tuning, model evaluation, and prompt engineering.
- Knowledge of enterprise security, governance, and responsible AI practices.
- Exposure to containerization, Kubernetes, CI/CD, and scalable deployment patterns.
- Prior leadership of AI/ML teams or technical initiatives.
**Required Education & Certifications**
- Graduate‑level degree in Computer Science, Engineering, or related technical field.
- Relevant certifications in AI/ML, cloud platforms, or MLOps are advantageous but not mandatory.