Job Description
Position Overview :
We are seeking a highly skilled and innovative AI Developer with expertise in Large Language Models (LLM) , vision modeling, production-ready frameworks, and Python programming to join our dynamic team. This role is ideal for individuals passionate about advancing AI technologies and applying their skills to develop cutting-edge solutions. As an AI Developer at our company, you will play a pivotal role in designing, developing, and deploying production-grade AI applications and systems that leverage both language and vision models to solve complex problems and deliver value to our organization and partners.
Key Responsibilities :
- Design and implement AI solutions using Large Language Models (LLMs), including both commercial (e.g., OpenAI GPT, Anthropic, Gemini) and open-source models (e.g., LLaMA, Mistral). This includes customization, fine-tuning, and integration into production pipelines to meet specific project requirements.
- Develop computer vision and multimodal AI solutions such as SAM, DETR, Vision Transformers, and integrate them with LLMs for applications that require both visual and language understanding.
- Build applications and services with production-ready frameworks (LangChain, LlamaIndex) to integrate LLMs into broader systems and workflows, enhancing their utility and effectiveness.
- Write robust, efficient, and maintainable Python code, following best practices in software engineering and AI system integration.
- Collaborate with cross-functional teams, software engineers, data analysts, graphic designers and other members of management, to define project specifications, identify challenges, and devise innovative solutions.
- Stay abreast of the latest advancements in AI, language models, and related technologies, and evaluate their applicability to current and future projects.
- Conduct rigorous testing and validation of models and applications to ensure accuracy, scalability, and resilience under real-world conditions.
- Provide technical guidance and support to team members, contributing to their growth and the overall success of the project.
- Document development processes, architectures, and decisions to ensure clarity, maintainability, and long-term system sustainability.
Required Skills and Qualifications :
Bachelor's degree in Computer Science, Data Science, Statistics, or a related field. Advanced degrees (MS or PhD) or equivalent work experience are preferred.Proven expertise in developing, fine-tuning, and deploying Large Language Models (LLMs) in production environments, including integration into retrieval-augmented generation (RAG) pipelines and enterprise workflows.Strong proficiency in Python programming, with experience in software development and AI model integration.Demonstrable experience with LLM orchestration frameworks such as LangChain or LlamaIndex for creating, managing, and deploying language model–powered applications.Familiarity with containerization technologies (e.g., Docker, Kubernetes) and DevOps practices.Solid understanding of machine learning concepts, natural language processing (NLP), and their practical applications.Ability to work in a fast-paced, collaborative environment and manage multiple projects simultaneously.Proficient and comfortable with software development within an Azure cloud infrastructureExcellent problem-solving skills and the capacity to think creatively and outside the box.Strong verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.Local Candidates OnlyApplicants must be authorized to work in the United States without the need for current or future sponsorship.Desirable Skills / Knowledge :
Experience with cloud computing platforms (Azure preferred; AWS, GCP also valuable) and their AI / ML services.Familiarity with modern DevOps / MLOps practices, including CI / CD pipelines, monitoring, and model lifecycle management.Python programming.Experience working with both commercial LLMs (e.g., OpenAI GPT, Anthropic Claude, Google Gemini) and open-source models (e.g., LLaMA, Mistral).LangChain, PyTorch, LlamaIndex, or similar frameworks.Advanced prompt engineering, structured output design, and evaluation techniques.Strong background in Retrieval-Augmented Generation (RAG), including design and optimization of retrieval pipelines.Vector databases (GCP Vector Search, ChromaDB, Pinecone, PQ Vector, or similar).Experience with computer vision and multimodal AI (SAM, DETR, Vision Transformers), and integrating visual and textual models in applied solutions.