Technical Lead, Central AI Lab

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🕒 May 6

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Vesta Software Group

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏢 Enterprise

🤝 B2B

Software • Enterprise • B2B

Vesta Software Group is a global organization specializing in the acquisition and long-term growth of vertical market software companies. Unlike traditional acquirers, Vesta operates on a buy-and-hold strategy, maintaining the independence of the companies they acquire and investing in their sustainable growth. Vesta prides itself on never selling a business, instead prioritizing the autonomy of its acquired companies and leveraging a network of resources to accelerate growth. With more than 30 acquisitions and a presence in over 9 countries, Vesta supports its portfolio companies with best practices and capital while fostering a productive and positive workplace culture, demonstrated by its Great Place To Work® certification.

📋 Description

• 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.

🏖️ Benefits

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