Role Overview:
The LLM Engineer will join an existing development team to enhance and expand a complex, dynamic application. The role requires strong communication skills and technical expertise across the stack. You will collaborate with global teams spanning multiple time zones and actively contribute to ongoing feature development.
An ideal candidate:
Executes both planning and hands-on technical work independently.
Collaborates effectively with Product Owners and other stakeholders to solve complex problems.
Works cross-functionally to contribute to impactful solutions across teams
Continuously develops technical expertise and stays up-to-date with new technologies.
Is passionate, intellectually curious, and driven to expand skills and knowledge.
Uses a data-driven approach to solve technical challenges and make informed decisions.
Applies systems-level thinking, integrating both data science and engineering principles.
Takes full ownership of the features and projects, delivering high-quality solutions on your own.
Must-Have Skills:
Strong experience with Python, particularly in building REST APIs using frameworks like FastAPI or Flask.
Expertise in microservices architecture and deployment in containerized environments (e.g., Docker, Kubernetes).
Strong knowledge in AI, machine learning, and natural language processing
Strong experience working with key LLM models APIs (e.g. OpenAI, Anthropic) and LLM Frameworks (e.g. LangChain, LlamaIndex)
Experience with MCP, Model Context Protocol.
Understanding of multi-agent systems and their applications in complex problem-solving scenarios.
Experience with RAG concepts and fundamentals (vectorDBs, semantic search, etc.)
Expertise in implementing RAG systems that combine knowledge bases with generative AI models.
Experience with prompt writing for various use cases
Experience with generative solutions released to prod, at scale, beyond POCs
Proficiency with server-side events, event-driven architectures, and messaging systems.
Strong problem-solving skills and experience debugging and optimizing backend systems.
Solid understanding of security best practices for backend systems, including authentication and data protection.
US/Canada based (preferably eastern time zone)
Other Qualifications:
2+ years of experience developing and experimenting with LLMs
8+ years of experience developing APIs with Python
Nice-to-Have Skills:
Experience with LLM guardrails
Experience with LLM monitoring and observability
Experience developing AI/ML technologies within large and business critical applications