Senior Engagement Lead

Job title: Senior Engagement Lead

Location: Fremont, CA - 2-3 days hybrid

Contract W2

About the role

We are hiring a Senior Engagement Lead to be our single onsite presence at a client in California, representing a remote delivery team based in India. You will be the voice of the client within our team and the face of our team within the client.

You will embed with business users, absorb their context, pain points and organizational nuance, and translate it into clear direction for sales, solutioning and offshore delivery. You will work in a product-led, agile environment, where success is measured by outcomes, adoption and client satisfaction.

This role suits a consultant who is technically credible in AI, fluent in agile and product ways of working, and comfortable operating on their own without a local team around them.

Key responsibilities

Voice of the client (onsite)

•Act as the single onsite representative of the India-based delivery team at the client site.

•Embed with business users’ day to day: shadow their workflows, join their routines and gather context informally, not only through formal meetings.

•Absorb business context, user pain points and organizational dynamics, and translate them back to sales, solutioning and delivery teams.

•Be the first point of contact for client questions, concerns and new ideas, and route them quickly to the right people.

Onsite–offshore bridging

•Structure overlap hours between US and India time zones and consistent daily handoffs.

•Keep async communication disciplined: clear written handoffs, logged decisions and tracked open questions, so nothing is lost between onsite context and offshore execution.

•Guide the offshore team, resolve blockers, and provide necessary context they cannot get remotely. Agile and product-led delivery

•Deliver using Scrum, actively participating in sprint ceremonies and backlog refinement.

•Align delivery with client Product Owners, product roadmaps, and priorities.

•Drive product engineering through scalable design, reusability, and engineering best practices.

•Focus on outcomes, user adoption, and business value.

•Demonstrate progress through working software, regular demos, and iterative releases.

•Use client tools such as Jira/Azure DevOps, Confluence, and Slack/Teams.

• Proactively identify and resolve risks, dependencies, and blockers with client & offshore teams.AI solutioning and account growth

•Frame business problems as AI opportunities with clear, measurable outcomes.

•Shape the right approach for each problem, from classical ML to generative AI, LLMs and agentic systems, with the offshore architects.

•Support pre-sales: discovery, solution shaping and effort estimation.

•Pitch solutions and new ideas for client stakeholders, from technical teams to CXOs.

•Spot opportunities to expand the account with new AI use cases. Client success

•Own the outcome of client expectations met and exceeded, tracked through regular feedback.

•Calibrate expectations early and continuously, so there are no surprises on scope, timing or results.

•Drive value realization and user adoption after each release, not just delivery.

•Act as a trusted advisor to client stakeholders at senior and working levels and handle difficult conversations transparently.

Required experience

•10+ years of overall experience in Data and AI, including significant time in client-facing consulting or engagement roles.

•Strong hands-on background in building data and AI solutions, deep enough to be technically credible with client architects and the offshore engineering team.

•Proven experience as the onsite lead for offshore or distributed delivery teams, ideally India-based.

•Agile delivery track record using Scrum, SAFe or Kanban, including running or taking part in sprint ceremonies.

•Product management fluency: working with Product Owners and PMs, product roadmaps, backlog-driven prioritization and outcome-based measures.

•Business analysis depth: eliciting requirements and writing user stories and acceptance criteria that remote teams can execute from.

•Strong stakeholder management with client business users, product leaders and executives.

•Track record of solutioning AI business problems and translating business needs into practical technical direction.

•Experience in pre-sales and pitching solutions and ideas to customers.

•Excellent written and oral communication, including concise async written updates that work across time zones.

Technical expertise

The role needs strong technical credibility rather than day-to-day building. You should be able to shape solutions, challenge designs and earn the trust of engineers.

•Machine learning and deep learning: supervised and unsupervised methods, NLP, computer vision, forecasting.

•Generative AI: LLMs, retrieval-augmented generation (RAG), prompt engineering, fine-tuning and AI agents.

•Languages and frameworks: Python and LangChain or similar.

•Cloud AI platform: Azure (Azure ML, Azure OpenAI).

•Data foundations: data engineering, Azure data platform.

•MLOps / LLMOps: model deployment, monitoring, evaluation and lifecycle management.

•Responsible AI: security, privacy, explainability and bias considerations.

•Delivery tooling: Jira or Azure DevOps, Confluence, Slack or Teams.

Personal attributes

•Comfortable with ambiguity, and able to create structure where none exists.

•Influences without authority, across both client and internal teams.

•Operates independently and confidently as the only team member onsite, without a local team for support.

•High ownership and a client-first mindset, with the judgement to know when to escalate.

•Culturally fluent across US and Indian working styles.

•To adhere to ISMS Policies and procedures

Good to have

•Domain exposure to semiconductor or manufacturing.

•Agile or product certifications, such as CSM, PSM, SAFe or CSPO.

•Microsoft Azure AI or data certifications.

•Experience building an AI practice, including offerings, accelerators and partner relationships.

•Thought leadership through publications, conference talks or community contributions.

Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Statistics, Mathematics or a related field.

•An MBA is a plus but not required.