Senior GenAI Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Design and develop scalable applications utilizing Generative AI and agentic AI, managing the entire process from start to finish.

• Create workflows powered by LLMs and devise prompt strategies for adaptive, self-learning multi-agent systems.

• Construct intelligent AI agents using LangChain and LangGraph for NL-to-SQL, autonomous task agents, and RAG pipelines.

• Choose, tailor, fine-tune, and enhance cutting-edge LLMs.

• Design and oversee complete ML/GenAI pipelines, encompassing training, deployment, monitoring, and lifecycle management.

• Develop APIs, microservices, and integration frameworks to incorporate AI into enterprise solutions.

• Advocate for responsible AI practices by addressing hallucinations, bias, and reliability concerns.

• Collaborate directly with customers, product teams, and engineering to transform business requirements into robust AI architectures.

• Mentor engineers and contribute to the shaping of the long-term AI platform strategy.

• Engage in a customer-facing role that includes solution architecture, hands-on engineering, and client discussions.

⛳️ Requirements

• Over 6 years of experience in traditional ML, including a minimum of 2 years of hands-on experience with Generative AI.

• Extensive expertise in LLMs (such as GPT and comparable models), prompt engineering, and agentic systems.

• Practical experience with LangChain/LangGraph or other similar agentic frameworks.

• Proficient in Python, including API wrappers, third-party integrations, and internal tooling development.

• Strong foundational knowledge in Transformers, CNNs, and RNNs, with hands-on experience using TensorFlow, PyTorch, and Scikit-learn.

• Experience in NLP, embedding models, and vector databases.

• Hands-on involvement with OpenAI, Llama/Llama2, Azure OpenAI, and other open-source models.

• Background in designing distributed, cloud-native architectures, including microservices and REST APIs.

• Proficient in AWS, Azure, or GCP, along with Docker and Kubernetes.

• MLOps/LLMOps experience, covering training, deployment, monitoring, and lifecycle management.

• Exceptional communication skills, able to convey technical concepts to non-technical stakeholders effectively.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field.

• Ability to thrive in a fast-paced startup environment with a strong sense of ownership.

• Preferred: Experience in LLM fine-tuning techniques (LoRA, RLHF, PEFT).

• Preferred: Background in performance optimization (GPU/TPU acceleration, quantization, pruning, distillation).

• Preferred: Familiarity with AI observability and monitoring tools.

• Preferred: Knowledge of AI governance and compliance standards (GDPR, SOC 2).

• Preferred: Previous consulting or solution-architecture experience in delivering enterprise AI products.

• Preferred: Experience in the financial services, healthcare, or insurance sectors.

🏝️ Benefits

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and the possibility for remote work.

• Opportunities for professional development and continuous learning.

• A collaborative and inclusive work culture.

• Competitive salary and performance bonuses.