Who You Are
You're an AI Engineer with 2+ years of experience who understands that context engineering is
becoming the most important skill an AI engineer can develop.
You're passionate about building
intelligent systems that solve real-world problems and excited about mastering the art of
providing the right context to unlock LLM potential in complex, dynamic applications.
Responsibilities
● Build and integrate LLM-powered features including document generation, intelligent
assessments, and conversational agents
● Design voice AI pipelines for real-time speech processing and multi-language support
● Master context engineering - dynamically managing memory, retrieval, and information
flow across complex agent trajectories
● Create agentic workflows that can understand context and generate domain-specific
outputs
● Integrate with LLM APIs (OpenAI, Anthropic, etc.) and optimize model performance for
production use
● Collaborate with engineering teams to seamlessly integrate AI capabilities into
applications
Qualifications Required
● 2+ years of hands-on experience building AI systems in production environments
● Strong expertise in Python and LLMs, prompt engineering, and API integrations
(OpenAI, Anthropic, etc.)
● Proficiency in core AI/ML libraries (transformers, LangChain, PyTorch/TensorFlow)
● Experience building RAG systems and working with vector databases
● Understanding of agentic AI systems and multi-agent architectures
● Knowledge of speech technologies (STT/TTS) and NLP frameworks
● Familiarity with cloud platforms (AWS/Azure) and MLOps practices
Nice to Have
● Experience with voice AI applications and real-time audio processing
● Healthcare domain knowledge or experience with compliance requirements
● Background in fine-tuning LLMs or multilingual NLP models
● Python FastAPI experience for building AI-powered APIs
● Experience with multi-agent frameworks like LangGraph, CrewAI, or AutoGen