Provide technical pre - sales support and shape security strategies for key accounts. Build partnerships, contribute to proposals and customer presentations, and drive project success.
About the role
- Senior Pre Sales Engineer designing and delivering enterprise-grade AI solutions for Carbon3.ai. Engaging customers and ensuring AI systems deployment that drives transformation.
Responsibilities
- Engage with enterprise customers to understand business goals and map them to AI workflows.
- Architect RAG pipelines, fine-tuning strategies, and inference endpoint deployments using our key products.
- Collaborate with GTM and sales teams during pre-sales cycles, workshops, and proof-of-concepts.
- Implement, optimise, and deploy models using PyTorch, HuggingFace, LangChain, and NVIDIA Triton.
- Execute fine-tuning and evaluation of foundation models for domain-specific use cases.
- Package and deploy models into scalable inference endpoints (REST/gRPC APIs, containerised or GPU-accelerated environments).
- Build pipelines that connect structured and unstructured enterprise data into vector databases and embedding models.
- Design semantic search and retrieval strategies to maximise response accuracy and relevance.
- Ensure all data pipelines are secure, compliant, and performant at scale.
- Work closely with infrastructure and platform engineering teams for smooth deployments.
- Feed insights into the product roadmap and platform feature development.
- Act as a thought leader and trusted advisor to customers exploring applied AI adoption.
- Develop and maintain 3–4 reusable solution accelerators (templates, playbooks, code repos) adopted across projects.
- Reduce model deployment cycle time by >30% through automation, tooling, or platform improvements.
- Train or mentor at least 2 junior engineers or solution architects in AI delivery best practices.
- Contribute 2+ technical case studies, blog posts, or conference talks showcasing Carbon3.ai’s AI solutions.
- Support pre-sales activities resulting in measurable influenced ARR aligned with GTM metrics.
Requirements
- Experience working directly with enterprise customers and translating technical concepts into business value.
- Solid experience within AI/ML engineering, applied AI, or solutions engineering roles.
- Proven experience with: RAG pipelines (LangChain, LlamaIndex, Weaviate, Pinecone, Milvus, etc.)
- Fine-tuning LLMs (LoRA, PEFT, instruction-tuning, domain adaptation)
- Deploying inference endpoints at scale (Triton, HuggingFace Inference, Ray Serve, Kubernetes)
- Strong coding skills in Python (and ideally one of Go, Java, or C++).
- Deep understanding of vector databases, embeddings, and semantic search.
Benefits
- Competitive compensation and performance-linked rewards
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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