CH
Work At Home Rhode Island, United States
KubernetesAI
EM
Salary not disclosed
Check market pay for comparable AI Enablement Technical Lead roles before applying.
Role overview
Job description
At Electric Mind, Engineering is where strategy meets action. Our team helps organizations cut through complexity—aligning business ambition with technology execution to unlock real, lasting change. You’ll work alongside curious, driven people tackling high-impact challenges for everyone from scaling startups to global enterprises. Each engagement is different, pushing you to learn, adapt, and grow.
Electric Mind’s Technology Practice brings together deep engineering expertise, modern delivery disciplines, and pragmatic architectural thinking to help clients execute complex, mission-critical transformation. We design and implement scalable, secure, high-impact technology solutions that accelerate business outcomes.
About the Role
Act as the accountable Electric Mind (EM) technical leader across a number of client teams, for a large scale AI Enablement program. The Tech Lead owns the adoption approach to Electric Mind’s AI-enablement delivery method and coaches Client Tech Leads, QE Leads, and Architects as required so the AI adoption practices across the different client teams remain consistent . This role is distinct from a typical Tech Lead role: the Electric Mind Tech Lead owns the AI adoption across multiple client teams, whereas a typical tech lead owns the technical delivery. Our Technical Leads will work closely with the Program Engineering Lead to foster AI adoption and will escalate any issues or blockers to adoption that fall outside of their remit to the Engineering Lead.
What You’ll Do
Act as the single point of Electric Mind technical accountability across its assigned pods — the owner of technical direction and decisions for how the AI-enabled delivery method is adopted technically. As the technical accountability point, the Tech Lead must be able to:
Key Deliverables
Single point of Electric Mind technical accountability for AI Enablement across assigned client teams.
Own the Electric Mind approach to AI-Enablement across technical disciplines (Dev, QE, Architecture, ...).
Coaching of Client Tech Leads, QE Leads, and Architects.
Instill a review-based culture and provide guidance on discipline and practices.
Integration of QE discipline into the AI Enabled lifecycle.
AI knowledge-base readiness, portability, and reusability.
Reporting of patterns (good and bad) across its assigned teams and escalation to the Engineering Lead.
What You’ll Bring
Senior technical leadership experience, capable of being the single point of technical accountability across multiple teams.
Strong understanding of how to apply AI Enablement methods for technology delivery teams.
Strong software engineering and architecture literacy . Familiarity with technical standards and industry best practices.
Ability to own and drive a technical adoption approach for a new (AI enabled) engineering method.
Working knowledge of AI-assisted engineering, agentic development harnesses, model behaviour, common AI failure modes and skills standards
Ability to coach senior technical roles — Tech Leads, QE Leads, and Architects — not just individual developers.
Experience in disciplined code reviews and documentation review practices.
Ability to distinguish a technical or architecture problem from a process, requirements, or delivery-management problem.
Comfort using AI tools to complete job functions.
Familiarity with SpecDriven development solutions is a plus.
About Electric Mind
Electric Mind is a fast-growing, AI-native advisory and digital engineering firm built for those who want to shape the future, not just watch it happen. We blend premium strategy expertise with cutting-edge AI-centric engineering to solve complex, meaningful problems for industry-leading clients.
We pride ourselves on a high-touch delivery model and a culture that values diverse talent, innovation, and true client partnership — creating an environment where your ideas matter and your impact is visible.
If you’re looking for a place where you can grow fast, collaborate with exceptional teammates, and help build a company scaling its capabilities and global footprint at speed — Electric Mind is the place to ignite your career. The future is bright!
For more info on Electric Mind, check out our Careers Page and Instagram.
Electric Mind is committed to diversity in the workplace. We are an inclusive employer and welcome and encourage applications from all qualified candidates. Applicants’ needs will be accommodated during our recruitment and selection process so please advise us if you require accommodation.
- Own AI adoption for the technical aspects of the Software Delivery Lifecycle : this comprises, but may not be limited to, how AI-assisted engineering, code, and QE practices are introduced, sequenced, and embedded across the client teams.
- Coach Client Tech Leads, QE Leads, and Architects as required, building their capability to foster adoption of AI enablement best practices within their own teams.
- Reinforce a review-based culture and make sure the processes around solution design review, code review, QE plan and test review are strong and disciplined, focused on correctness against acceptance criteria rather than style. As AI compresses authoring, review becomes the real bottleneck, and review discipline is frequently a pre-existing team weakness that must be addressed.
- Own accountability for the integration of the QE approach into the AI enabled lifecycle. E.g. where QE enters the delivery flow, how QE activities connect to solution design and implementation, and how AI-authored tests are used as the mechanism for instilling trust in AI-generated functionality.
- Own the approach to the build out of the technical artifacts that will be part of each solution’s AI knowledge-base. Ensure that these artifacts support implementation readiness, portability, and reusability so the team’s technical work can be reused rather than remaining a one-off local solution.
- Ensure AI-generated technical outputs respect engineering constraints, architecture, coding standards, repository structure, test requirements, and enterprise stack limits across its assigned pods.
- Make sure the right technical role owner (developer, QE, or architect) is accountable for technical, QE, architecture, or tooling issues, and step in where technical ownership is unclear.
- Surface AI Enablement patterns across assigned teams— such as recurring technical risks, architecture gaps, and inconsistent engineering or QE practice — so that they can be resolved across the program rather than in isolation.
- Escalate to the Engineering Lead when factors outside of the role’s remit block or impede the smooth adoption of AI Enablement practices.
About this listing
- Source: Electric Mind's official careers site (via Lever) · last confirmed on the source 30 Oct 2026
- Posted 4 Aug 2026
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What they are looking for
Skills & requirements
airecruitment
Qualification
We are an inclusive employer and welcome and encourage applications from all qualified candidates
Department · Engineering
Hiring company
Electric Mind
Technology
We are your expert partners in technology enabled solutions. Combining strategy, design, and engineering, Electric Mind transforms complex challenges into opportunities for growth and success. We partner with organizations to grow, run, protect, optimize, and transform their business.
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