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AI Innovation Lead

1 week ago

Karachi, Sindh, Pakistan Beam AI Full time

About Beam AI

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  • Beam AI is a cutting-edge tech start-up that leverages Generative AI and NLP to build intelligent agents for business operations. Our goal is to revolutionize productivity by automating repetitive tasks in seconds. Powered by LLMs, our agents are easy to set up, seamlessly integrate with business applications, and support teams where they need them most.

    We are on a mission to transform business practices by empowering organizations with artificial intelligence to increase efficiency, improve competitiveness, and scale operations globally.

About The Role">
  1. You will play a crucial role in the development, implementation, and optimization of our AI models and systems.
  2. You will work closely with other engineers and product teams to build intelligent systems that improve business processes through automation and data-driven insights.
  3. We seek an individual passionate about innovating and leveraging AI technologies to drive growth and efficiency.
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  • Research & Innovation: Investigate emerging AI techniques, including reasoning, planning, and memory architectures, to enhance AI Agents' autonomy and adaptability.
  • Feature Development: Design and implement new agent capabilities, such as function calling, multi-step task execution, and learning from feedback.
  • LLM Optimization: Leverage prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques to improve the performance and reliability of large language models (LLMs).
  • Agent Orchestration: Develop systems that allow AI Agents to break down complex tasks, collaborate with other agents, and request human input when needed.
  • Data & Workflow Integration: Work closely with data engineers and product teams to build robust pipelines for AI Agents to access structured and unstructured data.
  • Performance & Scalability: Optimize AI systems for efficiency, ensuring that agents can handle real-world constraints such as cost, latency, and interpretability.
  • Continuous Learning & Improvement: Stay updated with the latest advancements in AI, machine learning, and software engineering, incorporating cutting-edge research into practical applications.
  • Code Quality & Reliability: Participate in code reviews, testing, and deployment pipelines to ensure high-quality and maintainable AI features.