Technical Delivery Lead
Turing
Technical Delivery Lead
Turing
AI-matched, vetted software engineering services
Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com.
Technical Delivery Lead, Emerging
Role: Technical Delivery Lead, Emerging
Location: India
Experience Level: 12+ years in software engineering or technical consulting, including 5+ years leading enterprise data or AI delivery
Work Model: Full-time; India-based, working with distributed teams across the United States, India, and Latin America
Reports To: Head of AI Delivery
Turing Intelligence builds and deploys production AI systems for enterprise clients. Our delivery teams work directly in client environments, translating high-value business problems into reliable systems that can operate at enterprise scale.
The Emerging portfolio spans consumer goods, supply chain, real estate, manufacturing, media, and other complex operating environments. This role ensures that multiple concurrent engagements reach production on time, meet their commercial commitments, and create the confidence required to earn follow-on work.
This is a high-ownership role for a technical delivery leader who can move between architecture, staffing, delivery health, and commercial decisions. Engagement managers own the client relationship; you will own how the work is engineered, staffed, reviewed, and recovered when delivery moves off plan.
Establish a clear operating view across every active engagement, including delivery status, burn against plan, margin, staffing, technical risks, and client commitments. Identify issues early, intervene directly, and ensure recovery plans have accountable owners and measurable outcomes.
Set and enforce the technical review bar for production AI systems. Review architecture across retrieval, orchestration, evaluation, guardrails, observability, scalability, and security, and ensure every proposed SOW receives appropriate technical review before signature.
Build staffing plans for each active SOW, allocate engineers across competing priorities, reduce avoidable bench time through redeployment, and hire and calibrate engineers against a consistently high bar. Lead teams distributed across the United States, India, and Latin America.
Partner with pre-sales and engagement leaders on scoping, estimation, delivery plans, and change control. Challenge assumptions before commitments are made, protect delivery margin, and ensure client expectations match the work that can be staffed and delivered.
Work with the Chief AI Architect and platform leaders to apply shared architecture and evaluation standards, identify reusable components, and turn successful engagement work into capabilities that improve future delivery.
Create a delivery-health baseline for every Emerging account, including status, burn against plan, margin, and material risks. Put an FDE staffing plan in place for every active SOW and establish a technical review before every new SOW is signed.
Maintain Emerging delivery gross margin at or above 40%, prevent avoidable client escalations from reaching the GM without warning, reduce bench time through active redeployment, and contribute at least two reusable components to the Enterprise AI platform.
Portfolio-level accountability: This is not a single-project delivery role. You will oversee several engagements with different clients, technical risks, staffing constraints, and commercial commitments at the same time.
Hands-on technical leadership: This is not a PMO or governance-only position. You must be able to inspect architecture, challenge technical decisions, and guide teams through production issues. Candidates without recent hands-on engineering judgment are unlikely to be successful.
Commercial accountability: Delivery quality and margin are inseparable in this role. You will be expected to challenge weak estimates, manage change, redeploy capacity, and make difficult tradeoffs when client demand exceeds the funded scope.
Client-facing pressure: You will step into troubled engagements, surface uncomfortable facts early, and work with engagement leaders to reset plans without damaging client trust.
Distributed execution: The portfolio relies on teams across multiple regions and time zones. You must be comfortable making staffing and delivery decisions across the United States, India, and Latin America.
Enterprise delivery leadership: 12+ years in software engineering or technical consulting, including 5+ years leading enterprise data or AI delivery.
Portfolio and margin ownership: A track record of owning delivery outcomes and commercial performance across a portfolio of client accounts—not only a single project.
Recent production AI experience: Direct responsibility for shipping GenAI or machine-learning systems to production within the last two years.
Technical depth: Strong working knowledge of LLM and agentic architectures, including retrieval, orchestration, evaluation, guardrails, observability, and production operations.
Delivery and commercial discipline: Experience with estimation, technical SOW review, staffing plans, change control, delivery recovery, and managing to a P&L.
Leadership across seams: The ability to align engagement managers, pre-sales, architects, and distributed engineering teams while maintaining clear accountability for technical delivery.
Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.
Turing uses artificial intelligence to connect businesses with a global pool of over 3 million vetted software engineers from 150 countries for custom application development and on-demand software engineering. Clients specify the required skills, and the AI matches them to top engineers, speeding up hiring and project delivery while reducing recruitment effort. Engineers who pass Turing’s vetting gain access to high-paying remote jobs with a strong chance of repeat opportunities, reflected in a 99% rematch rate. The company differentiates itself by combining a large, pre-vetted talent pool with AI-driven matching to deliver fast, scalable engineering teams for businesses and steady remote work for engineers. Its goal is to accelerate project timelines for clients and provide reliable, well-compensated remote opportunities for engineers.
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