Delivery Module Lead

Mphasis; North Carolina; Híbrido; USD 180.000 - 260.000; Jornada completa

Descripción de la vacante

Mphasis is seeking a Go-To-Market Lead for AI products to drive adoption and execution across the enterprise. The role blends GTM leadership with hands-on engineering and customer enablement to accelerate GenAI deployments in real-world workflows.

You will partner with product, engineering, and business stakeholders to turn AI capabilities into measurable business value, building demos, reference implementations, and scalable enablement assets while maintaining a strong focus on governance and

Formación

• 4+ years of AI experience or equivalent
• 3+ years in go-to-market leadership, technical product, solution engineering, or forward-deployed engineering
• Hands-on experience building with GenAI/LLMs and agent-based systems
• Strong programming skills with modern stacks and APIs
• 3+ years of cloud platforms (GCP or Azure) and containerization (Docker, Kubernetes/OpenShift)

Responsabilidades

• Define and execute GTM strategies for enterprise AI capabilities, focusing on LLMs, agentic systems, and composable AI platforms
• Partner with business and engineering teams to design, prototype, and deploy GenAI and agentic solutions
• Lead workshops and create scalable enablement assets (SDKs, playbooks, prompt libraries)
• Translate business problems into GenAI architectures with patterns like RAG and multi-agent orchestration
• Establish tight feedback loops to influence platform roadmap and improve usability
• Communicate complex AI concepts clearly to technical and non-technical audiences
• Ensure governance, security, and responsible AI in deployments

Conocimientos

GTM leadership

Tech product

Forward deployment

Developer enablement

Stakeholder mgmt

Herramientas

GitHub Copilot

Devin

Cursor

APIs

Descripción del empleo

Go-To-Market Lead – AI Prod Mgr

We Are Seeking a Highly Technical, Product-oriented, And Customer-focused Individual To Drive Adoption And Delivery Of Generative AI And Agentic AI Capabilities Across The Enterprise. This Individual Will Function As a Blend Of

• Go-To-Market Leader – defining and executing adoption strategies for AI platforms and capabilities
• Forward-Deployed Engineer – working directly with business teams to prototype, build, and deploy AI-powered solutions in real-world workflows

You will play a critical role in turning emerging AI capabilities into tangible business impact, partnering closely with product, engineering, and line-of-business stakeholders to accelerate experimentation, deployment, and scale.

This role requires a strong bias for action, comfort with ambiguity, and the ability to leverage modern AI-native development tools to move from idea to working solution rapidly.

Responsibilities

• Go-To-Market Leadership & Adoption
  • Define and execute GTM strategies for enterprise AI capabilities, with emphasis on LLMs, agentic systems, and composable AI platforms
  • Drive adoption of APIs, agent frameworks, orchestration layers, and developer tools through targeted enablement and engagement
  • Lead feature launches and platform rollouts, translating technical capabilities into clear business value narratives
• Forward-Deployed Engineering & Solution Acceleration
  • Partner directly with business and engineering teams to design, prototype, and deploy GenAI and agentic solutions
  • Build hands-on demos, reference implementations, and rapid prototypes that showcase platform capabilities in real-world use cases
  • Engage in pair programming, debugging, and solution development, accelerating time from concept to production
  • Leverage tools such as GitHub Copilot, Devin, Cursor, and other AI-assisted development platforms to rapidly solve problems and iterate
• Customer Enablement & Developer Experience
  • Lead workshops, office hours, and hands-on sessions focused on building with LLMs, RAG architecture, and agentic workflows
  • Develop scalable enablement assets (SDKs, playbooks, reusable components, prompt libraries, agent templates)
  • Improve developer experience and time-to-value by identifying friction points and driving improvements across tooling and documentation
• Solution Strategy & Agentic Architecture
  • Translate business problems into GenAI and agentic solution architectures, incorporating patterns such as RAG, tool use, multi-agent orchestration, and memory frameworks
  • Partner with platform teams to define reusable design patterns, accelerators, and reference architectures
  • Stay at the forefront of GenAI, agentic systems, LLMOps, and emerging AI-native development paradigms
• Feedback Loop & Product Influence
  • Establish tight feedback loops with end users to shape platform roadmap and prioritize enhancements
  • Capture insights across deployments to inform improvements in usability, performance, and scalability of AI solutions
  • Champion a customer-first, experimentation-driven culture across AI initiatives
• Stakeholder Engagement & Communication
  • Act as a trusted advisor bridging technical depth and business strategy
  • Communicate complex AI concepts clearly to both technical and non-technical audiences
  • Deliver executive-ready updates highlighting adoption, business impact, and innovation outcomes
• Governance, Security & Responsible AI
  • Ensure adherence to responsible AI principles, model governance, data security, and regulatory requirements
  • Collaborate with risk, compliance, and security teams to operationalize safe and compliant AI deployments

Required Qualifications

• 4+ years of experience in Artificial Intelligence experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 3+ years in go-to-market leadership, technical product, solution engineering, or forward-deployed engineering roles
• Hands-on experience building with GenAI/LLMs and agent-based systems, including rapid prototyping and deployment
• Strong programming skills and experience working with modern development stacks and APIs
• 3+ years of experience with cloud platforms (GCP or Azure) and containerization (Docker, Kubernetes/OpenShift)

Desired Qualifications

• Deep expertise in Generative AI and agentic architectures, including: LLMs, RAG, embeddings, vector search
• Agent frameworks (LangChain, LangGraph, AutoGen, ADK, or similar)
• Tool use, orchestration, and multi-agent systems
• Experience leveraging AI-assisted development tools (e.g., GitHub Copilot, Devin, Cursor) to accelerate innovation and delivery
• Strong familiarity with LLMOps practices: prompt/version management, evaluation, observability, guardrails
• Experience building end-to-end AI applications, from prototype to production
• Proven ability to build demos, prototypes, and customer-facing solutions that drive adoption
• Experience in large-scale enterprise environments, preferably in regulated industries
• Strong communication and stakeholder management skills with ability to influence senior leaders
• Ability to operate as both a strategic leader and hands-on builder