AI Engineer

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About The Role

Senior AI Engineer

Agentic AI architectures

LLM-based systems

Key Responsibilities

• Design and develop agentic AI systems that leverage LLMs for reasoning, planning, and multi-step task execution.
• Implement LLM-based agents using frameworks such as LangChain, CrewAI, AutoGPT, or custom architectures.
• Fine-tune and prompt-engineer large language models (e.g., GPT, LLaMA, Claude) for domain-specific tasks.
• Integrate LLMs with external tools, APIs, databases, and retrieval systems (e.g., RAG pipelines).
• Collaborate with cross-functional teams to define agent behaviors, system flows, and performance benchmarks.
• Optimize model performance, cost, and inference latency across cloud or hybrid infrastructures.
• Stay current on emerging research and advancements in LLMs, AI agents, and autonomous systems.
• Contribute to internal documentation, technical blogs, and knowledge sharing sessions.
  

Required Skills & Qualifications

• 7+ years of experience in AI/ML engineering, including at least 2+ years working with LLMs and/or agentic AI systems.
• Proficient in Python and ML libraries (e.g., PyTorch, TensorFlow, Hugging Face Transformers).
• Deep understanding of LLM orchestration frameworks like LangChain, LlamaIndex, or similar.
• Strong experience building end-to-end AI solutions, including inference pipelines, evaluation, and deployment.
• Experience with prompt engineering, chain-of-thought reasoning, and tool-augmented LLMs.
• Knowledge of modern MLOps practices and cloud environments (AWS, GCP, Azure).
• Excellent problem-solving, system design, and communication skills.
• Self-starter comfortable working in a distributed, remote team.