Senior AI Engineer (LLM)

About the Role

The role of a Senior AI Engineer at Proxify is multifaceted, requiring a deep understanding of AI technologies, software development, and teamwork. Your day-to-day responsibilities will include designing and optimizing AI workflows, evaluating and implementing strategies for model selection, and developing high-performance Python backends to serve AI features to a global user base. If you thrive in an environment where innovation and collaboration are key, this role is an excellent fit.

Proxify's commitment to its members' success is reflected in its exceptional Glassdoor and Trustpilot ratings. As a Senior AI Engineer, you will be part of a global network of supportive, talented developers interested in remote full-time jobs. This role offers the opportunity to work with a company that values its employees' growth and well-being, providing a harmonious work-life balance and flexible withdrawal options.

What You Will Do

• Architect and implement complex AI workflows using frameworks like LangChain, LlamaIndex, or Haystack
• Design and optimize Retrieval-Augmented Generation (RAG) pipelines, including vector database management and advanced indexing strategies
• Evaluate and implement strategies for model selection based on latency, cost, and performance requirements
• Develop high-performance Python backends to serve AI features to a global user base
• Build robust evaluation frameworks to measure LLM accuracy, reduce hallucinations, and monitor production performance
• Work closely with product and engineering teams to identify high-impact AI opportunities and navigate the technical trade-offs of generative AI
• Collaborate with cross-functional teams to integrate AI solutions into the company's products and services
• Participate in the development of the company's AI strategy and roadmap
• Stay up-to-date with the latest advancements in AI and machine learning, applying this knowledge to improve the company's AI capabilities

What We Are Looking For

• Expert-level Python skills with a deep understanding of asynchronous programming and backend architecture
• Proven experience building and deploying production-level applications using Large Language Models (LLMs)
• Strong experience with SQL and NoSQL databases, specifically optimized for high-dimensional vector search
• Familiarity with deploying AI models in cloud environments (AWS, GCP, or Azure) and managing CI/CD for AI services
• A 'first-principles' approach to solving the unique challenges of non-deterministic AI outputs
• Experience with fine-tuning open-source models using techniques like LoRA or QLoRA
• Knowledge of agentic frameworks and autonomous AI agents
• A background in traditional NLP (Spacy, NLTK) or classic Machine Learning
• Excellent communication and teamwork skills, with the ability to collaborate with cross-functional teams

Nice to Have

• Experience with containerization using Docker and Kubernetes
• Familiarity with AI-specific frameworks and tools, such as Hugging Face Transformers or TensorFlow
• Knowledge of cloud-based AI services, such as Google Cloud AI Platform or Amazon SageMaker
• Experience with agile development methodologies and version control systems like Git
• A strong understanding of software development principles, including testing, debugging, and deployment

Benefits and Perks

• Competitive compensation package
• Flexible withdrawal options for easy access to your earnings
• Predictable project hours with a harmonious work-life balance
• Up to 24 flex days off per year without losing pay
• Career-accelerating positions at cutting-edge companies
• Hand-picked opportunities, personally matched to your skills and preferences
• One seamless process for endless opportunities, with no extra assessments
• Access to a global network of supportive, talented developers
• Opportunities for professional growth and development in a rapidly expanding field
• The chance to work with a company that values its employees' growth and well-being

• tip: Ensure your portfolio showcases your expertise in Python, asynchronous programming, and AI model deployment, highlighting specific examples of successful projects.
• tip: Familiarize yourself with the latest advancements in AI and machine learning, and be prepared to discuss how you apply this knowledge in your work.
• tip: Develop a deep understanding of the company's products and services, and be prepared to discuss how your skills and experience align with their goals.
• tip: Practice explaining complex technical concepts in simple terms, as effective communication is key in this role.
• tip: Research the company's culture and values, and be prepared to discuss how you embody these principles in your work.
• tip: Be prepared to discuss your experience with agile development methodologies and version control systems, and how you apply these principles in your work.
• tip: Consider highlighting any experience you have with cloud-based AI services, such as Google Cloud AI Platform or Amazon SageMaker, as this can be a valuable asset in this role.