Technical Lead, AI Lab

Position: Technical Lead, Central AI Lab
Job Description:

Technical Lead, Central AI Lab  The Vesta Software Group acquires, manages, and builds software companies in a variety of vertical markets, enabling them to be clear leaders in their industries. Our companies provide mission-critical enterprise solutions for vertical industries across the entire industry value chain. The Vesta Software Group Limited is all about strengthening businesses within the markets in which we compete and enabling them to grow – whether through organic measures such as new initiatives and product development, day-to-day business, or through acquisitions.
Position Build and ship production-grade AI capabilities that can be reused across Vesta Business Units (BUs). You will lead by example as a hands‑on engineer, set the engineering bar, and turn pilots into repeatable starter kits with strong Dev Ops, security, and handover discipline.
This role is not "R&D" and not "just prototyping". The goal is measurable delivery in 90‑day cycles, then reuse  Responsibilities   Reusable "starter kits" aligned to the AI-First Strategy build plan (e.g., Maintenance automation kit, AI-SDLC kit, Commercial/Sales acceleration kit).
Production-ready pilots with clear monitoring, evaluation, runbooks, and BU handover.
Reference architectures and implementation patterns that work across heterogeneous BU stacks (Azure, AWS, on‑prem, legacy products).
Technical leadership (hands‑on):
Own end‑to‑end solution design and implementation for central pilots and reusable components.
Lead technical discovery with BUs: 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 supporting change management efforts during transition.
Engineering excellence and delivery:
Build full‑stack capabilities: APIs, integrations, data flows, UI surfaces where required, and LLM application layers (agents/RAG/workflows).
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.
AI‑SDLC and governance‑by‑design:
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).
Mentorship and enablement:
Coach junior engineers and partner engineers on modern SDLC, Dev Ops, and pragmatic AI delivery.
Contribute to internal playbooks, templates, and show‑and‑tell case studies.
Job Qualifications   Must-have experience: 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 Dev Ops 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.
Nice-to-have:

Experience with modernization patterns (strangler, wrappers, service extraction).
Exposure to Model Context Protocol (MCP) or similar context/tooling integration approaches.
Experience shipping customer‑facing support automation, voice workflows, or knowledge systems.
Experience in vertical market software or…