The ideal candidate is hands-on with AI systems engineering, has experience integrating multiple models and runtimes, and is passionate about building secure, scalable, and efficient AI solutions that power next-generation agentic applications.
Responsibilities
Hybrid AI Agent Development: Architect, build, and optimize AI agents that run seamlessly across device and cloud environments.
MCP Service Integration: Leverage and extend MCP services to enable flexible orchestration, tool integration, and agent coordination.
Agentic Routing & Planning: Implement routing logic and reasoning strategies to improve decision-making and planning across multi-agent and multi-model systems.
Model Runtime Engineering: Work with different model runtimes, frameworks, and backends to maximize performance.
Security & Compliance: Ensure model safety, sandboxing, data governance, and secure execution across device and cloud.
Optimization: Apply techniques like model quantization, pruning, distillation, and caching for efficiency across diverse environments.
Technical Evangelism: Contribute to best practices, design patterns, and technical documentation to support broader adoption of hybrid AI agent architectures.
2+ years hands-on experience on AI/ML algorithm development
1+ years of hands-on experience in NLP, LLM-based systems, or AI agent development.
Deep expertise in GenAI algorithms, solution architecture, and performance tuning.
Proven experience building custom AI tools, agents, or apps for real-world use cases.
Strong Python or C++ skills.
Excellent problem-solving skills with a results-driven, customer-focused mindset.
Familiarity with client AI tools, cross-platform agents, or plugin ecosystems.
Preferred skills:-
Experience with RAG pipelines, vector databases (e.g.,FAISS, Chroma), and embedding techniques.
Experience optimizing GenAI workloads for edge devices using xPU accelerators.
Experience with local LLMs (e.g., Mistral, Llama) or fine-tuning open-source models.
Experience in customer/partner support for GenAI workflow design and deployment.
Experience with frameworks such as LangChain, LlamaIndex, AutoGen, HuggingFace, and other APIs.
Experience in UX/UI or prompt engineering to improve human-AI interaction.
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