AI Engineer

• Architect and build scalable Generative AI and agentic AI applications end to end
• Design LLM-powered workflows and prompt strategies for reflexive, self-learning, multi-agent systems
• Build intelligent AI agents using LangChain and LangGraph for NL-to-SQL, autonomous task agents, and RAG pipelines
• Select, customize, fine-tune, and optimize state-of-the-art LLMs
• Design and own full ML/GenAI pipelines, including training, deployment, monitoring, and lifecycle management
• Build APIs, microservices, and integration frameworks to bring AI into enterprise products
• Champion responsible AI practices by mitigating hallucinations, bias, and reliability risks
• Partner directly with customers, product, and engineering to translate business needs into robust AI architecture
• Mentor engineers and help shape long-term AI platform strategy

• 6+ years in traditional ML, including 2+ years hands-on with Generative AI
• Strong experience with LLMs (GPT and similar), prompt engineering, and agentic systems
• Real-world experience with LangChain/LangGraph or similar agentic frameworks
• Strong Python skills — API wrappers, third-party integrations, internal tooling
• Solid foundation in Transformers, CNNs, RNNs
• Hands-on with TensorFlow, PyTorch, Scikit-learn
• Experience with NLP, embedding models, and vector databases
• Hands-on work with OpenAI, Llama/Llama2, Azure OpenAI, and other open-source models
• Experience designing distributed, cloud-native architectures (microservices, REST APIs)
• Proficiency with AWS, Azure, or GCP, plus Docker/Kubernetes
• MLOps/LLMOps experience — training, deployment, monitoring, lifecycle management
• Excellent communication skills — ability to translate technical depth for non-technical stakeholders
• Bachelor's or Master's in CS, Data Science, Engineering, Math, Statistics, or related field
• Comfort with startup pace and strong ownership mentality
• Preferred: LLM fine-tuning experience (LoRA, RLHF, PEFT)
• Preferred: Performance optimization (GPU/TPU acceleration, quantization, pruning, distillation)
• Preferred: AI observability/monitoring tool experience
• Preferred: Familiarity with AI governance and compliance (GDPR, SOC 2)
• Preferred: Prior consulting or solution-architecture experience shipping enterprise AI products
• Preferred: Background in financial services, healthcare, or insurance