Leadership - Agentic AI Solution Architect
5 days ago
Position Overview
We are seeking a highly skilled Generative AI Solution Architect with hands-on experience in Agentic AI frameworks and Small Language Models (SLMs), along with deep expertise in AI/ML and data engineering in industrial contexts. This role will design, architect, and deploy scalable AI-driven solutions that leverage generative models, SLMs, autonomous agents, and robust data pipelines to transform operations in manufacturing, oil & gas, transportation, energy, smart infrastructure, and related verticals.
You will be responsible for bridging state-of-the-art generative and agentic AI with operational efficiency at scale—deploying solutions in cloud, hybrid, and industrial edge environments.
Key Responsibilities
1. Generative AI, SLM & Agentic AI Solution Architecture
- Lead end-to-end design and deployment of generative AI systems using LLMs and SLMs, integrated with Agentic AI workflows for autonomous reasoning, planning, and execution in complex industrial environments.
- Select and fine-tune Small Language Models for domain-specific tasks (predictive analytics, operational assistance, workflow automation) that require low latency, reduced cost, privacy, and edge deployment.
- Architect multi-agent systems where SLMs serve as specialized reasoning components within larger orchestration frameworks.
- Ensure architectures meet industrial constraints—including compute resource limits, security, redundancy, and real-time responsiveness.
2. Industrial AI/ML & Data Engineering Integration
- Design and implement scalable AI/ML workflows incorporating structured/unstructured data from sensors, IoT devices, time-series databases, and vision systems.
- Build data ingestion, cleaning, transformation, and feature store pipelines optimized for both generative AI and SLM training/inference.
- Leverage hybrid architectures that integrate edge inference (for SLMs) with centralized LLM-based services for decision support and large-context reasoning.
- Enable continuous learning pipelines with domain-specific fine-tuning and retraining of both LLMs and SLMs.
3. Agentic AI & Multi-Agent Systems Development
- Architect and deploy multi-agent solutions using:
- NVIDIA NIM™, NeMo™, and Agentic AI Blueprints
- AWS Bedrock / SageMaker with agent orchestration
- Azure OpenAI Service with cognitive skills & plugins
- Google Vertex AI Agents
- Open source frameworks: LangChain, Semantic Kernel, Haystack, Ray Serve for distributed orchestration
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