
11 - 50 employees
đŒ Consulting
đ Manufacturing
đŠ Logistics
Consulting âą Manufacturing âą Logistics
VALIS is a technology company specializing in advanced software solutions for the scrap metal recycling industry. They provide cutting-edge tools such as VALI-Sort, VALI-Sample, and VALI-Melt designed to optimize scrap metal sortation, quality analysis, and recycling processes. With a focus on empowering scrap processors and melt facilities, VALIS integrates artificial intelligence to deliver actionable insights and improve operational efficiency. In addition to software, they offer consulting and research services to help businesses maximize profitability, quality, and sustainability in their recycling processes. Their solutions bridge the gap between teams and processes within the recycling value chain, facilitating data-driven decision making and reducing human error.
đ„ 19 minutes ago
đ Portugal, United Kingdom, +4 more countries â Remote
â° Full Time
đŽ Lead
đźââïž Software Engineering Manager
đ» Ghost score 15%
Where this job comes from
Posted on VALIS's careers page, not through a job board
First seen by Remote Rocketship 19 minutes ago

11 - 50 employees
đŒ Consulting
đ Manufacturing
đŠ Logistics
Consulting âą Manufacturing âą Logistics
VALIS is a technology company specializing in advanced software solutions for the scrap metal recycling industry. They provide cutting-edge tools such as VALI-Sort, VALI-Sample, and VALI-Melt designed to optimize scrap metal sortation, quality analysis, and recycling processes. With a focus on empowering scrap processors and melt facilities, VALIS integrates artificial intelligence to deliver actionable insights and improve operational efficiency. In addition to software, they offer consulting and research services to help businesses maximize profitability, quality, and sustainability in their recycling processes. Their solutions bridge the gap between teams and processes within the recycling value chain, facilitating data-driven decision making and reducing human error.
âą Own architecture of the org brain and personal brain, including data ingestion, knowledge storage, retrieval, agents, and integrations with Claude and other LLMs âą Write code hands-on where it matters most âą Design access control, data retention and deletion, GDPR compliance, and multi-tenancy âą Build MCP servers and connectors to Slack, Google Workspace, Asana, HRIS, DWH, ERP, and other company systems, enabling client self-service âą Lead complex technical conversations âą Own the technical side of deployments âą Productize client-specific solutions to avoid repeated custom work âą Serve as the final technical escalation point âą Lead cloud infrastructure, CI/CD, observability, and security across AWS/GCP and Cloudflare âą Own the data stack, including Redshift, MotherDuck/DuckDB, ETL, and large-scale migrations âą Manage platform costs, token and inference spend, subscriptions, and vendor negotiations âą Hire, develop, and dismiss engineering team members âą Build an engineering culture focused on outcome ownership and limited day-to-day management âą Use AI agents such as Claude Code as the main working tool and establish them as the team's main tool
âą 10+ years in software engineering, including 4+ years as CTO, VP Engineering, Head of Engineering, or Principal/Staff Engineer at a product company or a strong startup âą Track record of building systems from zero to production with real users and real load, built hands-on rather than only led teams âą Deep hands-on experience running LLMs in production, including agents, RAG, tool use and MCP, evals, and cost control âą Strong backend architecture and data engineering, including distributed systems, integrations, data stores, security and access control âą Experience managing an engineering team, including hiring and firing âą Ability to explain technical decisions to clients' non-technical executives and win their support âą Fluent English âą Good working knowledge of RU language âą Experience in B2B SaaS, enterprise deployments, or forward-deployed engineering âą Experience with company data such as HRIS, ERP, finance, and organisational structure âą Strong personal AI productivity setup
âą Competitive base âą Performance-based bonus âą Opportunity to join the team during fast growth
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