Technical Lead, Central AI Lab

Role Overview

• Build and ship production-grade AI capabilities that can be reused across Vesta Business Units (BUs).
• Lead by example as a hands-on engineer, set the engineering bar, and turn pilots into repeatable starter kits with strong DevOps, security, and handover discipline.
• Deliver reusable "starter kits" aligned to the AI-First Strategy build plan (e.g., Maintenance automation kit, AI-SDLC kit, Commercial/Sales acceleration kit).
• Produce production-ready pilots with clear monitoring, evaluation, runbooks, and BU handover.
• Create reference architectures and implementation patterns that work across heterogeneous BU stacks (Azure, AWS, on-prem, legacy products).
• Own end-to-end solution design and implementation for central pilots and reusable components.
• Lead technical discovery with BUs, focusing on constraints, data readiness, integration points, and security requirements.
• Support adoption of AI-DLC (AI driven Development Lifecycle) methodology across Portfolio BUs by leading by example and aiding change management efforts during transition.
• Establish CI/CD patterns for AI-enabled systems (tests, security scanning, release gates, environment separation).
• Drive reliability: observability, cost controls, latency, fallbacks, and safe failure modes.
• Operationalize AI-DLC/AI-SDLC practices: spec-first delivery, eval harnesses, quality gates, and auditable artifacts.
• Ensure solutions can be safely operated by BUs with minimal central dependency (docs, runbooks, dashboards, training).
• Coach junior engineers and partner engineers on modern SDLC, DevOps, and pragmatic AI delivery.
• Contribute to internal playbooks, templates, and show-and-tell case studies.

Requirements

• 7+ years building and operating production software systems (SaaS, enterprise, or similar).
• Strong SDLC fundamentals: testing, code review, CI/CD, release management, incident thinking.
• Proven ability to design secure systems: authN/authZ, secrets management, audit/logging, least privilege.
• Strong backend engineering (APIs, data stores, async patterns) and comfort going "full stack" when needed.
• Cloud and DevOps competence (AWS and/or Azure; containers; infrastructure automation).
• Practical experience integrating AI/LLM capabilities into products or workflows (does not need to be "AI researcher" background).
• Ability to operate across varied tech environments (legacy + modern), with high autonomy and good stakeholder communication.
• Experience with modernization patterns (strangler, wrappers, service extraction) is nice-to-have.
• Exposure to Model Context Protocol (MCP) or similar context/tooling integration approaches is nice-to-have.
• Experience shipping customer-facing support automation, voice workflows, or knowledge systems is nice-to-have.
• Experience in vertical market software or multi-product portfolios is nice-to-have.

Tech Stack

• AWS
• Azure
• Cloud
• SDLC

Benefits

• Optional international travel (USA/Canada/South America) for portfolio events.
• Travel: Occasional UK travel for BU workshops, onboarding, and group events.