Senior GenAI 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 turn business needs into robust AI architecture




• Mentor engineers and help shape the long‑term AI platform strategy




• Serve in a customer‑facing role spanning solution architecture, hands‑on engineering, and client conversations

Requirements

• 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 — you can 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

Core Competencies

Demonstrates expertise in architecting and building scalable Generative AI applications, with a strong focus on LLMs, prompt engineering, and ML pipeline management. Proficient in developing intelligent AI agents and integrating AI solutions into enterprise products while ensuring responsible AI practices.

Highest‑signal resume keywords

• Generative AI Development




• LLM Prompt Engineering




• LangChain/LangGraph Frameworks




• Python Programming




• MLOps Lifecycle Management

Hard Skills

• Generative AI




• LLMs




• Prompt Engineering




• LangChain




• LangGraph




• Python




• TensorFlow




• PyTorch




• NLP




• MLOps

Soft Skills

• Excellent Communication




• Mentoring

Certifications & Qualifications

• Bachelor's in CS




• Master's in Data Science

Industry Keywords

• AI Governance




• Compliance




• Financial Services




• Healthcare




• Insurance

Tools & Technologies

• AWS




• Azure




• GCP




• Docker




• Kubernetes




• OpenAI




• Llama




• Vector Databases




• APIs




• Microservices