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The role
This is a rare opportunity to be first in the door to continue the development of our engineering platform. You will own a production system end to end — the web application, the database estate, the data pipelines, the deployments, the integrations and the LLM serving stack. You will be working in the energy sector utilising your skills to provide tenanted platforms to Optimise Engineering Systems, Field Service Management and Asset Optimisation.
What’s involved?
- Genuine full-stack breadth in one codebase: a React/TypeScript application, a Postgres estate with 100-million-row telemetry tables, serverless functions, MQTT ingestion from building management systems.
- LLM model training in the specialist fields our clients value most. It could be a housing estates network or a shopping centre, each LLM is tailored to their exact use case.
- Applied LLM Models that are fine-tuned and on served on our own hardware, doing real triage on real faults — you will run its training cycles, evaluation gates and serving estate, hands on the whole loop from corpus to production.
- Neural LLM-assisted engineering at the sharp end: coding agents are a first-class part of how the platform is built, and you will get very good at directing them, verifying them and knowing where they lie.
- Operational technology: BACnet, Trend, JACE and Tridium controls, data points all working together to optimise and commission real engineering systems.
- The energy transition, concretely: heat networks are central to UK decarbonisation and growing fast; the domain knowledge you build here is scarce and compounding.
- Small-company reality: direct access to clients, sites, commercial decisions and the CEO, we are a bureaucracy free organisation with a. clear delivery and results focus.
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What you will do
- Operate the LLM estate: run LoRA fine-tuning cycles and evaluation gates on Elevate’s GPU hardware, manage vLLM serving (including multi-adapter deployments) alongside production, promote or roll back model versions on the gate results, and keep the serving watchdogs healthy. The CEO retains model direction; this role owns the running of the pipelines.
- Develop, deploy and maintain the Helios web application (React, TypeScript, Vite) and its offline-first engineer mobile surface, with serverless functions on Vercel and Database including the email-ingestion and messaging pipelines.
- Own the data layer: Postgres on Database — schema design, row-level security for tenant isolation, SQL functions, materialized views, scheduled jobs, query performance at telemetry scale.
- Run the telemetry pipeline: MQTT ingestion from site BMS equipment, collector services, data-quality rollups, retention, and the monitoring that guards them.
- Test and verify to the house standard: every change exercised end-to-end against production, the automated invariants suite kept green and extended with each feature.
- Participate in site connection work: commissioning the BACnet-to-MQTT link with the field team when new networks are onboarded.
Qualifications and experience
Essential
- Degree in computer science, software engineering or a related discipline, or demonstrably equivalent professional experience.
- ML operations capability: comfortable operating model-serving infrastructure and running established training and evaluation pipelines on Linux/GPU hardware — process management, resource monitoring, versioned promote/rollback. Training pipelines exist and are documented; you must be able to run, monitor and recover them, not design them from scratch.
- Five or more years building and running production web applications full-stack, with sole or lead ownership of at least one system in live use.
- Strong TypeScript and React; strong SQL and relational schema design on PostgreSQL, including performance work on large tables.
- Serverless or cloud deployment experience (Vercel, AWS Lambda, Cloudflare Workers or similar) and comfort operating what you ship: logging, monitoring, incident response.
- API integration experience against third-party systems (REST, OAuth2/JWT, webhooks), including at least one messy real-world system of record.
- A testing discipline you can describe and defend: automated checks, verification against the live system, and honest reporting of what is and is not proven.
- Python for scripting, data processing or pipeline work.
- Right to work in the UK and willingness to travel occasionally to sites and client offices.
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Preferable
- Deeper LLM experience: fine-tuning methodology, corpus design, evaluation-harness construction, vLLM internals, or heavy daily use of AI coding agents.
- ERP, FSM or works-management domain experience — job lifecycles, scheduling, SLAs, parts, timesheets, invoicing — or heat-network / building-services domain experience (BMS, metering, HIUs, energy-centre plant).
- IoT or telemetry experience: MQTT, time-series data, meter or sensor fleets; BACnet or Trend/Tridium controls exposure a bonus.
- Supabase specifically (RLS policies, edge functions, realtime), and Deno.
- Mobile/PWA offline-first patterns; mapping (Leaflet); document generation.
- Experience in a small company or founder-adjacent role where you owned outcomes rather than tickets.
CV’s should be sent to recruitment@Elevateeverywhere.com with a covering letter.
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Skills
TypeScript
React
PostgreSQL
Python
MLOps
LLM Fine-tuning
vLLM
Serverless
MQTT
API Integration
SQL Schema Design
Linux/GPU Hardware
Vercel
BACnet
Testing Automation
Data Pipeline Management
Location