About Fetcherr

Fetcherr specializes in deep learning, algorithmic forecasting, and dynamic markets. The company is building a new generation of LLM-powered analytical systems that will transform how businesses interact with data.

As the Tech Lead for LLM Systems, you will architect and build Fetcherr’s LLM-based virtual analyst platform from the ground up. This is a highly technical, hands-on role focused on LLM architecture, RAG pipelines, prompt engineering, vector databases, and reliability infrastructure.

You’ll work with product, data, and engineering teams to design a powerful conversational analytics engine built on state-of-the-art LLM technologies.

Responsibilities

Architecture & System Design

• Architect end-to-end systems that combine:
• LLMs (commercial + open-source)
• Vector databases & embeddings
• Retrieval-augmented generation (RAG)
• Natural-language-to-SQL/query generation
• Visualization and analytics libraries
• Define the technical roadmap and system architecture for the LLM platform.

Hands-On Technical Execution

• Build prototypes, run experiments, evaluate LLM providers (OpenAI, Claude, Gemini).
• Develop and optimize:
• Prompt engineering & chaining
• RAG pipelines
• Query translation engines
• Auto-generated dashboards and visual outputs
• Ensure scalability, observability, security, and cost efficiency.

LLM Expertise & Innovation

• Lead research and experimentation for model selection, fine-tuning, context injection, and multi-agent tooling.
• Evaluate open-source vs. commercial LLMs and architect hybrid solutions.
• Define evaluation frameworks for accuracy, hallucinations, latency, and safety.

Organizational LLM productivity evangelist

• Lead the organizational adoption of AI tools for improving productivity and quality

Cross-Functional Technical Leadership

• Work closely with product managers and customers to shape use cases.
• Provide technical mentorship to LLM engineers, backend developers, and data engineers.
• Be the internal expert and advocate for LLM technologies across Fetcherr.

• Deep knowledge of LLM system architecture:
• RAG, embeddings, vector search
• Prompt engineering & prompt chaining
• Data-to-text generation & visualization tools
• Python, backend systems, cloud infrastructure (GCP preferred)
• Experience with LLM frameworks (LangChain, LlamaIndex, Hugging Face).
• Experience with APIs like OpenAI, Anthropic Claude, Gemini, etc.

Leadership & Product Thinking

• Experience delivering complex 0→1 AI systems.
• Ability to translate business needs into technical architectures.
• Strong communication skills for explaining LLM decisions and trade-offs.

Nice to Have

• Experience with BI/analytics or natural language interfaces to data.
• Knowledge of multi-agent systems or tool-augmented LLMs.
• Background in airline, pricing, or financial domains.