Senior Data Scientist

Location: Serbia, Armenia (We are ready to discuss other countries as well) 🏢 Remote work is possible

About the product At FlameTree, we are building a platform for creating AI agents that help businesses scale customer support, lead follow-up, and sales across multiple communication channels — both inbound and outbound. Our AI agents work with knowledge bases, communicate in real time, and drive conversions across messaging platforms. The platform supports 150+ languages and integrates with WhatsApp, email, and web applications, offering strong security and high scalability for business growth.

🎯Responsibilities: • Design and develop the core agent layer responsible for orchestrating interactions with LLMs. • Build and maintain complex conversational logic: state machines, agent workflows, and orchestration pipelines. • Control and shape LLM behavior: prompt design, structured outputs, deterministic flows. • Manage conversational context: memory, history, token limits, and degradation strategies. • Ensure reliability and predictability on top of inherently non-deterministic models. • Implement resilient integrations with LLM providers (timeouts, retries, fallbacks, multi-provider strategies). • Optimize latency and cost (streaming, batching, caching, token efficiency). • Debug complex production issues (inconsistent outputs, race conditions, state loss). • Contribute to system architecture: clear boundaries between agents, backend, and real-time components. • Build observability around LLM pipelines (prompt/response logging, tracing, quality metrics).

🎯Requirements: • 5+ years of backend development experience with strong Python skills (async, architecture, performance). • Proven production experience with LLMs (not side projects): understanding of limitations, cost, and behavior. • Experience building agent-based systems or complex orchestration logic (state machines, pipelines). • Ability to make LLM behavior predictable (structured outputs, schema validation, guardrails). • Strong debugging skills in non-deterministic systems. • Deep understanding of API integrations (timeouts, retries, idempotency, backpressure). • Experience optimizing latency and throughput in production systems. • Solid Docker experience and understanding of production environments. • Ability to make architectural decisions independently and take ownership. • Strong engineering mindset: writing maintainable, scalable, production-grade code.

🎯Nice to Have: • Experience with multi-agent systems, tool/function calling • Experience with local LLMs (Ollama, vLLM, GPU inference) • Experience with real-time / voice systems • LLM observability (prompt tracing, evals, quality metrics) • Cost optimization at scale for LLM usage

🎯What Makes This Role Interesting: • You will work on the core intelligence layer of the product — not just integrations. • Real production challenges: high load, low latency, reliability requirements. • Direct impact on system architecture and technical decisions. • Fast execution cycle — minimal bureaucracy. • Engineering-driven approach to LLMs (reliability, control, metrics — not just prompt tinkering). • Strong engineering team focused on building real systems, not prototypes.

🎯Who This Role Is NOT For: • Candidates without real production experience with LLMs • Engineers relying only on frameworks without understanding underlying mechanics • Developers without experience in high-load or latency-sensitive systems • People focused on quick hacks rather than building reliable systems