About Gruve
Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.
Position summary:
We are seeking a talented Senior Software Development Engineer to join our AI team. You will technically lead experienced software and machine learning engineers to develop, test, and deploy AI-based solutions, with a primary focus on large language models and other machine learning applications. This is an excellent opportunity to apply your software engineering skills in a dynamic, real-world environment and gain hands-on experience in cutting-edge AI technology.
Key Responsibilities:
- Architect and build scalable AI/ML solutions with a strong focus on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and deep learning architectures.
- Own the full AI lifecycle including data ingestion, document indexing, embedding generation, retrieval, preprocessing, training, fine-tuning, evaluation, and production deployment.
- Design, implement, and optimize RAG pipelines using vector databases and retrieval frameworks to enable accurate, grounded, and explainable AI responses.
- Apply advanced fine-tuning methods such as LoRA and Q-LoRA to optimize large models for business-specific use cases.
- Implement and experiment with reasoning models (e.g., DeepSeek-R1) and hybrid RAG + reasoning workflows for complex enterprise AI applications.
- Curate, clean, chunk, and manage high-quality structured and unstructured datasets for robust RAG and model training workflows.
- Evaluate and improve RAG systems using RAG-specific evaluation techniques such as retrieval accuracy, faithfulness, relevance, latency, and hallucination reduction.
- Optimize model and retrieval performance through embedding optimization, reranking strategies, inference tuning, compute optimization, and efficient resource utilization.
- Build automated MLOps and LLMOps pipelines for training, deployment, monitoring, drift detection, and continuous improvement of AI and RAG systems.
- Deploy AI and RAG solutions across cloud platforms (AWS, Azure, GCP) and explore edge deployments where required.
- Develop APIs and microservices to integrate AI and RAG capabilities seamlessly into enterprise applications.
- Ensure compliance with data security, regulatory standards, privacy requirements, and responsible AI practices.
- Collaborate with product, engineering, and business stakeholders to deliver AI-driven and RAG-powered business outcomes.
- Mentor junior engineers and promote best practices in AI, RAG system design, and software engineering.
- Stay current with emerging AI, LLM, and RAG research, and drive innovation across the team.
Basic Qualifications:
- Bachelor's, Master's, or PhD in Computer Science, Data Science, Engineering, or a related field.
- 5–8 years of hands-on experience in AI/ML engineering or related roles.
- Strong programming skills in Python.
- Solid understanding of machine learning fundamentals and deep learning concepts.
- Hands-on experience with ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
- Practical experience or strong familiarity with LLMs, transformer-based architectures, and RAG concepts.
- Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Milvus) and retrieval frameworks (e.g., LangChain, LlamaIndex) is a plus.
- Understanding of RAG evaluation techniques, prompt engineering, and grounding strategies is a plus.
- Familiarity with frontend development and frameworks such as React.
Preferred Qualifications:
- Excellent problem-solving skills and an eagerness to learn in a fast-paced environment
- Strong attention to detail and ability to communicate technical concepts clearly
Why Gruve
At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you're passionate about technology and eager to make an impact, we'd love to hear from you.
Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.