Key skills
Software EngineeringMachine LearningArtificial IntelligenceProduction LLM SystemsRetrieval-Augmented Generation (RAG)EmbeddingsRerankingVector DatabasesEvaluation Systems DesignQuantitative Model AnalysisPythonSystem ArchitectureProduction Systems ReliabilityCost ManagementAIMLLLMRAGChromaPineconeAnalyticsAirflowSaaSCommunication
About this role
Harnham is a high-growth, mission-driven SaaS company transforming how businesses build and maintain trust, with AI at the core of their next phase of innovation. The Senior AI Engineer role involves defining how AI is architected across the company and making foundational decisions around systems and long-term technical direction. Responsibilities include designing production AI systems, building scalable infrastructures, and partnering with teams to translate requirements into effective solutions.
Responsibilities:
- Design and own production AI systems end-to-end, including LLM pipelines, retrieval systems, and orchestration layers
- Build and scale RAG systems, reranking pipelines, and vector-based search infrastructure
- Define evaluation frameworks to measure retrieval quality, reasoning accuracy, and system performance
- Analyze production behavior, identify failure modes, and drive improvements based on data
- Make key architectural decisions across model infrastructure, tooling, and workflows
- Partner closely with product, platform, and domain teams to translate complex requirements into scalable systems
- Lead best practices for building reliable, observable, and cost-efficient AI systems
Requirements:
- 5+ years of software engineering experience, including 3+ years working on ML or AI systems
- Proven experience deploying production LLM systems
- Strong background in RAG, embeddings, reranking, and vector databases (e.g., Pinecone, FAISS, Chroma)
- Experience designing evaluation systems and improving models through quantitative analysis
- Strong Python skills, with solid software engineering fundamentals
- Experience making architectural decisions that influence team or org direction
- Strong understanding of production systems, including reliability, observability, and cost tradeoffs
- Ability to break down ambiguous problems and operate with a high degree of ownership
- Clear communication skills and experience working cross-functionally
- Experience in regulated domains such as compliance or security
- Familiarity with data platforms or analytics tooling
- Experience with orchestration frameworks (e.g., Temporal, Airflow)
- Exposure to LLM evaluation platforms or tooling
- Contributions to open source, research, or technical communities