AI Technical Lead

📋 Description

• • Own the end-to-end technical vision for AI engagements at TXI, translating ambiguous business problems into concrete, production-ready solutions that generate measurable ROI for clients across manufacturing, logistics, life-science, and nonprofit sectors.
• • Act as the primary technical voice in pre-sales conversations: craft tailored demos, architect rapid proof-of-concepts, and arm the demand team with crisp, jargon-free narratives that explain how large-language models, agentic systems, or vision AI can unlock new revenue, cut costs, or de-risk operations.
• • Lead cross-functional discovery sprints (2–8 weeks) that combine user research, data audits, feasibility spikes, and ethical-AI assessments to surface the highest-impact automation or augmentation opportunities—then shepherd those concepts through iterative delivery until KPIs are met or exceeded.
• • Stay hands-on in code: design data pipelines, fine-tune open-source or proprietary models, implement evaluation harnesses, and deploy containerized services to cloud or edge environments while mentoring junior engineers and pairing daily with designers, strategists, and delivery managers.
• • Champion responsible-AI practices—bias detection, explainability, privacy, security, and transparency—by embedding governance checkpoints into every stage of the product lifecycle and coaching client teams on how to sustain them post-launch.
• • Continuously scan the horizon for emerging techniques (e.g., retrieval-augmented generation, multi-modal agents, low-rank adaptation) and package your findings into internal tech talks, blog posts, and reusable accelerators that expand TXI’s collective knowledge and market differentiation.
• • Balance a fluid calendar that shifts between billable delivery (up to full-time in peak quarters) and non-billable sales enablement; communicate proactively with Delivery Managers to ensure staffing, scope, and expectations remain aligned.
• • Within your first 30 days, complete TXI’s immersive onboarding, shadow live client calls, and ship a small internal LLM-powered tool that demonstrates our engineering standards; by month 3, co-lead your first paid discovery engagement; by month 12, have at least one public case study and one repeatable AI accelerator to your name.
• • Foster an inclusive, feedback-rich environment where every teammate—regardless of role or seniority—feels safe to challenge assumptions, share half-baked ideas, and iterate toward excellence together.
• • Contribute to TXI’s employee-ownership culture by participating in quarterly business reviews, voting on strategic initiatives, and mentoring new hires so our collective expertise compounds over time.