AI/ML Lead

About the role:

We’re hiring an experienced AI/ML Engineer to lead the development of a high-performance, multi-agent AI system using AutoGen, GPT-4, and a tightly integrated set of generative and data intelligence APIs.

You’ll be building the system’s core intelligence layer — reasoning agents, tool integrations, knowledge retrieval, and multimodal generation — in a modular, API-first environment. This is a deep engineering role with full ownership of the agent orchestration logic, generative pipeline, and backend interface.

Responsibilities:

Core AI & Agentic System Development

• Design, develop, and maintain multi-agent reasoning workflows using AutoGen
• Build and configure agent roles (planner, researcher, generator, critic, etc.) with task-specific prompts and tool access
• Enable agent communication, memory sharing, reflection loops, and retry logic

LLM Integration & Prompt Engineering

• Integrate OpenAI GPT-4 Turbo via API with proper system message configuration, role memory, and adaptive chaining
• Handle token optimization, dynamic context management, and API response control
• Implement prompt templates for reasoning, estimation, generation, and critique agents

External API Integration

• Integrate and manage the following tools and APIs:
• Serper.dev or Brave API for real-time search and data retrieval
• Galileo AI or Uizard APIs for UI mockup generation
• Mermaid.js (rendered via LLM) for architecture and flow diagrams
• Runway ML Gen-2 API for generating concept/demo videos
• ElevenLabs API for voice narration (optional integration)

Required Skills:

• Proven experience (5+ years) in applied AI/ML development, including model design, training, and deployment.
• Strong proficiency in Python, PyTorch or TensorFlow, and relevant ML frameworks.
• Hands-on experience with LLMs, generative models, computer vision, or multimodal AI systems.
• Solid understanding of data engineering pipelines, vector databases, and API-based system integration.
• Familiarity with cloud infrastructure (AWS, GCP, or Azure) and scalable deployment strategies (Kubernetes, Docker, etc.).
• Experience integrating AI into interactive, collaborative web or design-based platforms is a strong plus.

Good to have:

• Familiarity with diagram generation (Mermaid, Graphviz, or similar)
• Experience using video or voice generation tools via API
• Understanding of LLM cost/latency optimization
• Exposure to multi-agent evaluation, self-critique loops, or scalable AI architecture