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An innovative firm is seeking a skilled software engineer to enhance their technology systems. This role involves designing software solutions, advocating for product quality, and optimizing technical processes. The ideal candidate will have advanced Python skills, experience with FastAPI, and a strong grasp of Langchain. You will collaborate with various teams to ensure high-quality deliverables while documenting solutions for clarity. Join a dynamic team focused on pushing the boundaries of technology and improving user experiences with cutting-edge solutions.
Participate in the processes of designing and planning software solutions.
Suggest ideas, new solutions, or improvements to the current technology systems.
Collaborate with the Pro and other stakeholders within Engineering (Frontend, UX, etc.).
Document the technical solutions with diagrams and necessary documents for easy understanding by other technical areas of the company.
Advocate for improvements to product quality, security, and performance.
Craft code that meets internal standards for style, maintainability, and best practices for a high-scale web environment. Maintain and advocate for these standards through code review.
Recognize impediments to team efficiency ("technical debt"), propose solutions, and implement improvements such as optimizing the LLM stack (cost, latency, route flow traceability, debugging with Langfuse).
Advanced Python, experienced with FastAPI.
Deep knowledge of Langchain.
Observability and debugging experience (Langfuse preferred).
Strong database knowledge (SQL, Redis).
Experience with asynchronous architectures.
Amazon Web Services knowledge.
SCRUM Methodologies practitioner.
Prompt engineering and LLM behavior tuning.
Experience with Node.js and NestJS.
Understanding of agent proxy architectures.
Familiarity with Websockets and streaming LLM responses.
Knowledge of vector search and RAG techniques (e.g., Pinecone, Qdrant).
Familiarity with LLM evaluation methods and tools (e.g., LangSmith, OpenAI evals).
Awareness of LLM-related security and compliance concerns.
Ability to manage cost, token usage, and latency of LLM calls.
Product thinking around user experience with LLM-powered features.
Experience with fine-tuning or hosting open-source models.