Generative AI Solutions Architect
Location : Bengaluru
Experience : 8 - 12 Years
Work Mode : Hybrid / On-site
Job Description
We are looking for an experienced Generative AI Solutions Architect to design, build, and deploy enterprise-grade Generative AI and AI/ML solutions. The ideal candidate should have strong expertise in LLMs, RAG, Python, AI/ML frameworks, cloud platforms, and modern GenAI architectures, along with experience providing technical leadership to engineering teams.
Key Responsibilities
- Design and implement enterprise-grade Generative AI and AI/ML solutions.
- Define AI strategies, technology roadmaps, and reference architectures.
- Architect and develop scalable RAG-based AI applications.
- Design solutions using LLMs, vector databases, embeddings, and semantic search.
- Evaluate and integrate appropriate AI/ML and cloud technologies.
- Provide technical guidance on Python, ML/DL, LLM, and GenAI frameworks.
- Mentor and guide AI Engineers, ML Engineers, Data Scientists, and development teams.
- Drive architecture and technical design reviews.
- Optimize AI solutions for accuracy, performance, scalability, security, and cost.
- Collaborate with business, product, data, and engineering stakeholders to translate requirements into AI solutions.
- Evaluate emerging technologies in Generative AI, Agentic AI, and LLM ecosystems.
- Establish best practices around AI engineering, deployment, monitoring, and responsible AI.
Mandatory Skills
- Generative AI / LLMs
- Python
- RAG
- Vector Databases
- LangChain
- Hugging Face
- Machine Learning / Deep Learning
- TensorFlow / PyTorch
- Cloud platforms - AWS / Azure / GCP
- AI/ML Solution Architecture
Good To Have
- Agentic AI / Multi-Agent Systems
- Prompt Engineering
- LLM Evaluation
- MLOps / LLMOps
- Knowledge Graphs
- Semantic Search
- Azure OpenAI / Amazon Bedrock / Google Vertex AI
- Enterprise AI governance and security
Preferred Candidate Profile
- Strong experience designing and delivering enterprise AI/GenAI solutions.
- Proven experience building RAG and LLM-powered applications.
- Strong understanding of cloud-native AI architectures.
- Excellent technical leadership and mentoring capabilities.
- Strong communication and stakeholder-management skills.
- Ability to work with senior leadership and guide enterprise AI transformation initiatives.
(ref:hirist.tech)
