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Digivance Solutions
Generative AI Architect
Digivance Solutions
Hyderabad•On-site•1-3 Yrs•1 hour ago
Job description
Overview
As a Technical Lead / Architect specializing in Generative AI, your role will involve architecting and leading the development of production-grade Generative AI & Agentic AI platforms.
Responsibilities
- Design enterprise-grade GenAI/Agentic AI systems & LLM-powered applications
- Build RAG pipelines, multi-agent collaboration systems, and autonomous workflows
- Implement prompt engineering, memory management, reasoning chains, and evaluation frameworks
- Lead end-to-end AI development from concept to production, while mentoring engineers
- Build CI/CD for AI, optimize inference performance, and ensure monitoring & governance
- Translate business problems into AI solutions and collaborate with product/engineering teams
- Design enterprise-grade GenAI/Agentic AI systems & LLM-powered applications
- Build RAG pipelines, multi-agent collaboration systems, and autonomous workflows
- Implement prompt engineering, memory management, reasoning chains, and evaluation frameworks
- Lead end-to-end AI development from concept to production, while mentoring engineers
- Build CI/CD for AI, optimize inference performance, and ensure monitoring & governance
- Translate business problems into AI solutions and collaborate with product/engineering teams
Qualifications
- Proficiency in Core AI & GenAI technologies including LLMs (OpenAI, Anthropic, LLaMA, Mistral), RAG, and LangChain/LlamaIndex
- Strong skills in prompt engineering, fine-tuning, embeddings, and guardrails
- Solid engineering background in Python, PyTorch/TensorFlow, and Hugging Face
- Knowledge of Cloud & Infrastructure technologies like Azure/AWS/GCP, Docker, Kubernetes, and GPU infrastructure
- Familiarity with MLOps practices including CI/CD for AI, model monitoring, drift detection, and observability
- Leadership abilities in leading AI teams, system design, problem-solving, and stakeholder management
- Proficiency in Core AI & GenAI technologies including LLMs (OpenAI, Anthropic, LLaMA, Mistral), RAG, and LangChain/LlamaIndex
- Strong skills in prompt engineering, fine-tuning, embeddings, and guardrails
- Solid engineering background in Python, PyTorch/TensorFlow, and Hugging Face
- Knowledge of Cloud & Infrastructure technologies like Azure/AWS/GCP, Docker, Kubernetes, and GPU infrastructure
- Familiarity with MLOps practices including CI/CD for AI, model monitoring, drift detection, and observability
- Leadership abilities in leading AI teams, system design, problem-solving, and stakeholder management