Head of Business Operations – Enterprise AI Deployment

- Location: India
- Company: Lambda Function
- Reporting to: Chief Executive Officer / Business Leadership

About Lambda Function Lambda Function is building the AI-native manufacturing platform for precision manufacturers.

Our mission is to enable autonomous precision manufacturing by applying AI across CNC programming, machining, quotation, quality, and sustainability.

We work with sophisticated aerospace, semiconductor, automotive, and other precision manufacturing organizations. Our enterprise engagements involve deploying AI into real-world manufacturing environments — requiring close coordination across customer engineering teams, data, AI models, software, and manufacturing processes.

The Role

We are looking for a Head of Business Operations to build and lead Lambda Function’s enterprise deployment engine.

When a customer purchases our Foundation Program, we take responsibility for establishing the data, manufacturing knowledge, AI models, workflows, and operational workplace required to successfully deploy our technology.

Today, much of this execution is handled by Product and Engineering. As we scale, we need a dedicated function that owns customer deployment from commercial handoff through successful go-live and transition into ongoing lifecycle management.

You will be the operational owner of the customer deployment.

Your mandate is simple

Make every enterprise deployment predictable, repeatable, high-quality, and successful — without requiring Product & Engineering to become the deployment organization.

This is a builder role. You will establish the processes, tools, operating rhythms, and eventually the team required to scale enterprise deployments from a handful of customers to dozens and ultimately hundreds.

What You Will Do

Own Enterprise Deployment

- Take ownership of customer engagements immediately following commercial close.
- Translate the SOW into a detailed implementation plan with milestones, owners, dependencies, and acceptance criteria.
- Coordinate customer Manufacturing Engineering,



IT, Operations, and leadership stakeholders.
- Drive data / knowledge acquisition, AI model development and validation, software deployment, training, and go-live.
- Own customer acceptance and transition into ongoing Model Lifecycle Management.

Build the Deployment Operating System Create a repeatable playbook covering:

- Customer onboarding
- Data and knowledge acquisition
- Model development and validation
- Deployment readiness
- Customer acceptance
- Training and enablement
- Go-live
- Post-deployment handoff
- Model Lifecycle Management

The objective is to move from “every deployment is a custom project” to “we have a proven deployment system.” Orchestrate Product & Engineering

- Translate customer requirements into clear internal actions.
- Manage technical dependencies against customer commitments.
- Determine when Engineering involvement is required and ensure it is focused and efficient.
- Prevent customer deployments from becoming unmanaged interruptions to Product & Engineering.

Drive Customer Outcomes

Track and improve

- Time-to-go-live
- On-time deployment
- Model / deployment quality
- Customer adoption
- Programming time reduction
- Customer acceptance
- Customer satisfaction
- Engineering effort per deployment

Who You Are We are looking for a high-ownership operator and builder who thrives at the intersection of customers, technology, and execution.

Required

- 7–12+ years in business operations, enterprise implementation, technical program management, professional services, customer success, or similar roles.
- Experience managing complex B2B enterprise deployments.




- Demonstrated ability to build processes and operating systems from scratch.
- Exceptional project management, communication, and stakeholder management skills.
- Comfortable working directly with senior enterprise customers.
- Strong bias toward action and accountability.
- Comfortable operating in a fast-moving startup with significant ambiguity.

Strongly Preferred

Experience with

- Manufacturing / industrial technology
- Aerospace, semiconductor, automotive, or precision manufacturing
- CNC / CAM / CAD / PLM / MES
- Industrial AI / ML deployments
- Enterprise SaaS implementation
- Digital transformation / Industry 4.0

Manufacturing engineering experience is a significant advantage.

What We Value

Builder mentality. You enjoy turning recurring heroics into repeatable processes.

Extreme ownership. When something is at risk, you ask “What needs to happen to fix it?” rather than “Whose responsibility is this?”

Customer obsession. You care deeply about whether the customer actually achieves value — not simply whether the project was technically completed.

Technical curiosity. You don’t need to be the deepest AI or manufacturing expert, but you must be able to understand complex technical environments and work credibly with engineers and manufacturing professionals.

What Success Looks Like

Within 6–12 months, Lambda Function has a repeatable enterprise deployment engine where:

- Foundation Programs consistently launch and complete on schedule.
- Customers have clear expectations and accountability.
- Deployment risks are identified early.
- Product & Engineering involvement is structured and predictable.
- Customers reach productive use quickly.
- Foundation Programs transition cleanly into Model Lifecycle Management.
- Deployment volume can increase significantly without proportional growth in engineering overhead.

This is not a project management role. It is an opportunity to build the operating system through which Lambda Function delivers AI into the world’s most sophisticated manufacturing environments.

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