Rust Backend Architect solving and validating production - grade backend systems for Gramian Consultancy’s AI training projects. Designing architectures, tests, and reliable concurrent services.
About the role
- AI Engineer building LLM-powered procurement and automation features for Remarcable’s trade-contractor software platform. Shipping RAG, agentic workflows and document intelligence into production.
Responsibilities
- Design, build and ship LLM-powered features across the platform, including invoice and PO matching, quote and document extraction, catalog normalization and smart purchasing suggestions
- Build RAG and agentic workflows using procurement, inventory and accounting data
- Own features end to end from prototyping through production rollout, monitoring and customer-feedback-driven iteration
- Partner with Data Engineering to use the data lakehouse for AI features and an internal AI assistant
- Build and maintain embedding pipelines, vector search and APIs serving web and mobile applications
- Integrate with model providers such as Anthropic and OpenAI, selecting models based on quality, latency and cost
- Create evaluation sets and automated tests to measure accuracy
- Monitor production AI features for accuracy, cost, latency and drift, and resolve issues
- Implement guardrails for data privacy, security and customer trust
- Work with Product Managers to identify high-value AI workflows for contractors and suppliers
- Help Customer Success, Support and internal teams automate manual work
- Share knowledge through documentation, demos and code reviews
- Lead or support AI-assisted AP automation, customer natural-language assistant and AI-powered supplier onboarding projects
- Report to the VP of Engineering and collaborate with Product, Data and Full Stack Engineering teams
Requirements
- 4+ years of software engineering experience, including at least 1–2 years building and shipping LLM or machine learning features to production
- Strong Python skills and experience building production APIs and services
- Hands-on experience with LLM APIs, prompt design, RAG, embeddings and vector databases such as pgvector, Pinecone or OpenSearch
- Experience building evaluations and measuring model quality
- Solid SQL and data skills; comfortable working with messy, real-world business data
- Experience with cloud infrastructure, preferably AWS, CI/CD and observability
- Clear communication skills and ability to explain AI trade-offs to non-technical teammates and customers
- Comfortable working with ambiguity and performing both strategic and hands-on work
- Experience with agent frameworks, tool use or MCP integrations
- Document AI experience, including OCR and extraction from invoices, quotes, packing slips or drawings
- Familiarity with construction, trades, procurement, ERP or accounting systems
- Experience with lakehouse or modern data stack tools such as Databricks, Snowflake or dbt
- Experience at a high-growth startup or scale-up, ideally in B2B SaaS
- Experience fine-tuning or hosting open-source models
Benefits
- Competitive salary and performance-based bonus
- Comprehensive health and wellness benefits
- Collaborative, mission-driven culture
- Opportunity to be one of the first dedicated AI engineers and shape how AI is built
- Work on real problems with real data from major electrical contractors
- See work used on jobsites, warehouses and purchasing offices within weeks
- Opportunity to join a high-growth company at an early stage and advance as the company scales
- Work closely with leadership on meaningful initiatives
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