Senior Python Engineer

Firehorse, a US-based company specializing in advanced AI technologies, is seeking a Senior Python Engineer with strong programming fundamentals and extensive expertise in both traditional machine learning and generative AI, including large language models (LLMs). The ideal candidate is someone who works efficiently, writes clean and well-tested code, and possesses a deep understanding of how AI models function internally. This role involves designing, building, and maintaining robust Python services and AI-driven features, with close collaboration alongside clients and stakeholders to deliver high-quality solutions.

Key Responsibilities

- Design, develop, and maintain scalable Python services, APIs, and data pipelines that support AI-powered applications.
- Implement AI features leveraging both traditional machine learning models and generative AI/LLM systems.
- Build and evaluate LLM pipelines, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and model evaluation.
- Write comprehensive end-to-end test cases to ensure high automated test coverage and maintain code quality.
- Rapidly prototype and iterate on solutions, balancing speed with reliability and maintainability.
- Optimize applications for performance, scalability, and robustness in production environments.
- Participate actively in code reviews and uphold best engineering practices across the team.
- Collaborate directly with clients and stakeholders to understand requirements and shape technical solutions accordingly.

Required Qualifications

- Minimum of 5 years of professional experience in Python development.
- Strong foundation in programming and computer science principles, including data structures, algorithms, and clean coding practices.
- Proven expertise in AI and LLM technologies, covering both traditional ML frameworks (such as scikit-learn and PyTorch) and generative AI tools (including Anthropic/OpenAI APIs, agent frameworks, and RAG systems).
- Deep understanding of AI model architectures, training processes, inference mechanisms, and evaluation techniques. This knowledge is essential.
- Hands-on experience building retrieval-augmented generation (RAG) systems, including working with retrieval pipelines and vector databases.
- Proficiency in writing end-to-end and integration tests, preferably using tools like pytest.
- Experience developing and consuming RESTful APIs and familiarity with Git version control workflows.
- Ability to work at a high velocity, quickly learning new concepts, delivering results independently, and owning project outcomes.

Preferred Qualifications and Benefits

- Experience deploying open-source AI models using platforms such as Hugging Face, vLLM, Ollama, or GPU-based inference solutions.
- Familiarity with cloud environments, particularly AWS, and containerization technologies like Docker and Kubernetes.

The company offers compensation paid via USD remittance, along with additional benefits including a fuel allowance and company-sponsored lunch. Employees receive double their daily salary for approved work on weekends or public holidays. The work schedule is hybrid, requiring three days in the office and two days remote. Firehorse fosters a culture free of micromanagement, encouraging direct interaction with stakeholders and empowering engineers to take ownership of their work.