Carnot Research is hiring a Senior GenAI/LLM Engineer (35 years experience)
We're expanding our AI engineering leadership as we scale next-generation agentic systems, multimodal platforms, and high-performance LLM services. If you bring deep experience in GenAI along with strong foundations in system design, distributed architectures, and microservices, this role will put you at the forefront of building production-grade AI systems.
*Responsibilities*
- Design, architect, and deliver scalable GenAI systems using agentic frameworks such as LangChain, LlamaIndex, CrewAI, or AutoGPT for complex workflow automation.
- Lead the development of advanced RAG architectures incorporating hybrid retrieval, context optimization, and high-throughput vector search.
- Own model adaptation processes, including LoRA/QLoRA fine-tuning, dataset curation, evaluation, and deployment to optimized inference stacks.
- Architect microservices-based LLM applications with robust APIs, observability, autoscaling, CI/CD pipelines, and cost/performance governance.
- Implement fault-tolerant LLM orchestration layers with fallback strategies, multi-model routing, caching, and latency optimization.
- Collaborate across product, engineering, and research teams to design end-to-end AI-driven solutions aligned with business goals.
- Develop evaluation frameworks, regression testing suites, and quality monitoring pipelines for continuous model improvement.
- Build multimodal experiences integrating text, vision, speech, and agentic reasoning capabilities.
- Stay current with emerging GenAI research and drive adoption of state-of-the-art methods into production systems.
*Requirements*
- 35 years of experience in GenAI, ML engineering, or AI-driven application development.
- Expertise with LLM APIs (OpenAI, Anthropic, Google, open-source models) and deep familiarity with transformer internals.
- Hands-on experience with agentic frameworks and complex workflow orchestration.
- Strong command over system design, distributed systems, microservices, architectural patterns, and production reliability principles.
- Proficiency with vector databases such as Pinecone, Weaviate, Qdrant, or Chroma.
- Experience with fine-tuning frameworks like Hugging Face, Axolotl, or similar.
- Strong Python engineering background with async programming, API development, error handling, and testing practices.
- Understanding of embeddings, semantic search, few-shot prompting, and structured reasoning.
- Experience building and maintaining production-grade AI systems with metrics, tracing, and monitoring.
- Desirable: multimodal AI, speech/voice systems, GPU optimization, or model serving infrastructure.
*What We Offer*
- Ownership of high-impact AI systems powering real-world products at scale.
- Opportunities to architect and guide cutting-edge solutions including agentic platforms, voice interfaces, and multimodal systems.
- Full exposure to the AI development lifecycle from research to deployment.
- A collaborative culture with ML researchers, engineers, and product teams.
- Access to compute, tooling, and experimentation resources required for advanced R&D.
- Competitive compensation, equity options, and flexible work arrangements.
- A fast-paced environment where your contributions directly influence product and customer outcomes.
