Delivery Lead

Company Description

Rapyder is a fast-moving AWS Premier Partner offering full-stack migration, modernization, GenAI, Managed Services, Snowflake, and Crowdstrike Solutions. With deep vertical expertise, Rapyder helps startup-to-large enterprises to move faster with less friction. We are trusted by several businesses for delivering innovative cloud solutions and ensuring seamless operations.

Role Title:

Delivery Practice Lead – AI/ML Innovation & Application Development

Immediate Joiner Only

Role Description

This is a full-time on-site role based in Bengaluru for a Delivery Practice Lead – AI/ML Innovation & Application Development. The Delivery Practice Lead will be responsible for leading the AI/ML practice, developing and implementing cutting-edge AI/ML solutions, managing AI/ML projects, and ensuring timely delivery. The individual will also play a crucial role in client engagements, team management, and collaborating with cross-functional teams to drive innovation.

Reporting To: Chief Delivery Officer (CDO)

Location: Bengaluru

Key Responsibilities

1. Delivery Leadership & Execution Excellence

• Own end-to-end delivery of AI/ML and AppDev engagements (Discovery → Build → Deploy → Optimize).

• Govern delivery outcomes using metrics-driven frameworks — quality, velocity, cost optimization, and customer satisfaction.

• Establish delivery blueprints and reusable templates for AI projects (e.g., MLOps pipelines, data prep, model lifecycle management).

• Ensure every solution aligns with enterprise-grade standards for scalability, security, and compliance.

• Champion DevSecOps, CI/CD, and observability practices across AI & app development projects.

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1. Practice Development & Innovation

• Build, scale, and mentor a cross-functional team of data scientists, ML engineers, and application developers.

• Establish an AI Innovation Lab / Tech Studio to incubate accelerators, reusable frameworks, and proof-of-concepts (POCs).

• Drive creation of IP-led offerings — e.g., agentic AI assistants, predictive maintenance models, generative AI workflows, and intelligent apps.

• Partner with cloud providers (AWS, Azure, GCP) and ISVs to integrate cutting-edge tools and reference architectures.

• Track technology trends (LLMs, multimodal AI, vector DBs, RAG architectures) and translate them into client-ready solutions.

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1. Business Growth & Customer Engagement

• Support sales & pre-sales by providing technical leadership during solutioning, scoping, and proposal defense.

• Collaborate with client CXOs and product leaders to shape AI-driven transformation roadmaps.

• Identify upselling and cross-selling opportunities within existing delivery accounts — e.g., AI Ops, data modernization, or workflow automation.

• Act as the executive sponsor for key projects ensuring strong stakeholder alignment and proactive risk management.

• Represent the practice in client presentations, analyst briefings, and thought leadership forums.

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1. Operational & Financial Governance

• Define and manage practice-level P&L, utilization targets, and margin optimization.

• Build and track delivery dashboards covering SLA adherence, project profitability, and team productivity.

• Enforce standard operating procedures (SOPs) for estimation, risk, and change management across AI & app development projects.

• Collaborate with the PMO and CDO to ensure continuous process improvement and delivery automation.

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1. Talent Leadership & Capability Building

• Lead a growing team (50–100+) of AI engineers, data scientists, app developers, and delivery managers.

• Define career pathways, skill matrices, and competency frameworks for AI & innovation tracks.

• Partner with HR & L&D to launch continuous learning programs — GenAI certifications, MLOps mastery, cloud-native development.

• Foster a culture of innovation, experimentation, and measurable outcomes.