Technical Delivery Lead, Emerging

About [Employer]

[Employer]’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, [Employer] 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, [Employer] is the largest and longest-running data provider in the category. [Employer] 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, [Employer] 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 [link removed]

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

Why Join [Employer] Intelligence?

[Employer] 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.

As the Technical Delivery Lead, Emerging, You Will

Own Portfolio Delivery Health

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.

Assure Architecture and Production Readiness

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.

Lead Distributed Forward-Deployed Teams

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.

Shape Scope, Estimation, and Commercial Commitments

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.

Turn Delivery into Platform Leverage

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.

How Success Will Be Measured

First 90 Days

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.

First Year

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.

The Anti-Sell

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.

Our Technical Delivery Leaders Typically Have

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.

Top-Tier Candidates Will Have

• Experience leading forward-deployed or client-embedded engineering teams in an AI, data, or technology-services organization.
• Experience in consumer goods, supply chain, real estate, manufacturing, media, or another operationally complex enterprise environment.
• A record of turning client-specific delivery work into reusable platform components, delivery accelerators, or technical standards.

Values

• We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
• We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
• We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.

Advantages of joining [Employer]

• Work at the frontier of AI, helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.
• Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.
• Bring frontier AI innovation to the enterprise, applying lessons learned from leading AI labs to solve real-world business challenges.
• Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies.
• Move at the pace of AI innovation, with the speed, ownership, and impact of a startup.

 

[Employer] 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 [Employer] 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 [Employer]'s GDPR notice here.