Senior Python Engineer

About the Company

Firehorse, a US-based company, is hiring a Senior Python Engineer with strong programming fundamentals and deep AI expertise spanning both traditional machine learning and generative AI / LLMs. We are looking for someone who moves fast, writes clean and well-tested code, and has a genuine understanding of how models work under the hood.

About the Role

Firehorse is seeking a Senior Python Engineer to design, build, and maintain robust Python services and AI-powered features, with a focus on both traditional ML and GenAI/LLM systems, while collaborating closely with clients and stakeholders and upholding engineering best practices.

Responsibilities

• Design, build, and maintain robust Python services, APIs, and data pipelines.
• Develop AI-powered features using both traditional ML models and LLM / GenAI systems.
• Build and evaluate LLM pipelines — prompt engineering, RAG, fine-tuning, and model evaluation.
• Write end-to-end test cases and maintain high automated test coverage.
• Prototype and iterate quickly — ship at a high pace without sacrificing quality.
• Optimize applications for performance, reliability, and scalability.
• Participate in code reviews and uphold engineering best practices.
• Collaborate directly with clients and stakeholders to shape technical solutions.

Qualifications

• 5 years of professional Python development experience.
• Strong programming and computer science fundamentals — data structures, algorithms, and clean code.
• Strong AI and LLM skills across both traditional ML (e.g., scikit-learn, PyTorch) and GenAI (e.g., Anthropic / OpenAI APIs, agent and RAG frameworks).
• Solid understanding of how models actually work — architectures, training, inference, and evaluation. This is a must.
• Hands-on experience building RAG systems — retrieval pipelines, vector databases, and evaluation. This is a must.
• Experience writing end-to-end and integration tests (e.g., pytest).
• Experience building and consuming REST APIs; fluency with Git workflows.
• High velocity: able to learn fast, deliver fast, and own outcomes independently.

Preferred Skills

• Open-source model deployment experience (e.g., Hugging Face, vLLM, Ollama, GPU inference).
• Cloud experience (AWS) and containerization (Docker / Kubernetes).

Compensation & Benefits

• Compensation through USD remittance.
• Fuel allowance and company-sponsored lunch.
• Double daily salary for approved weekend or public-holiday work.
• Hybrid schedule — 3 days in office, 2 days remote.
• No micromanagement; direct interaction with stakeholders.