Senior Forward Deployed Engineer; AI

Math Co is an AI and analytics consultancy headquartered in Chicago with a major hub in Bangalore. We help global enterprises turn data, analytics, and AI into measurable business outcomes, with over 2,000 projects delivered across industries. We don't stop at strategy: we build what we design, and we measure what we build.

Forward Deployed Engineering is our answer to how AI is changing consulting. The highest leverage person is no longer a project manager, an architect, a data scientist, or a developer. It is the one person who connects all of these while staying closest to the customer's problem.

AI is changing how consulting delivers value.

At Math Co, our Forward Deployed Engineers sit at the intersection of business strategy, AI, software engineering, and client delivery. They are not specialists working within a narrow function. They are end-to-end problem solvers who partner directly with clients to transform ambiguous challenges into deployed, measurable outcomes.

As a Senior Forward Deployed Engineer (AI), you will embed with client teams, understand their business problems, architect scalable solutions, build production-ready systems, and guide adoption through deployment and handoff. You will serve as the primary technical owner throughout the engagement lifecycle, ensuring every decision remains tied to business value.

You will operate across AI, data, cloud, software engineering, and stakeholder management to deliver solutions that clients trust and scale.

Our approach begins with a simple principle:

• Collaborate closely with client stakeholders to understand business objectives, workflows, and decision-making processes.
• Identify opportunities where AI, analytics, and data-driven solutions can create measurable impact.
• Separate assumptions from facts and establish a clear understanding of the problem before solution design begins.
• Define success metrics and align stakeholders on expected outcomes.
• Design scalable, secure, and production-ready architectures aligned with client technology ecosystems.
• Evaluate technical trade-offs and guide architectural decisions across cloud, data, AI, and application layers.
• Ensure solution designs account for security, governance, integration, scalability, and operational requirements.
• Document architectural decisions and implementation approaches clearly.

• Develop and deploy production-grade AI, analytics, and software solutions using real-world client data.
• Build reusable, maintainable, and scalable code across the solution stack.
• Implement GenAI-enabled capabilities, including retrieval-augmented generation (RAG), agentic workflows, evaluation frameworks, and orchestration mechanisms.
• Validate solution effectiveness through structured testing and measurable performance outcomes.
• Lead discovery workshops, solution reviews, working sessions, and executive presentations.
• Communicate technical concepts effectively to both business and technical audiences.
• Proactively identify risks and trade-offs while providing actionable recommendations.
• Manage scope, priorities, timelines, and stakeholder expectations throughout the engagement.

• Operational runbooks
• Validation and testing evidence
• Knowledge transfer materials
• Ensure successful adoption by client teams and support transition to production ownership.
• Continue providing architectural guidance during scaling and implementation.

• Leverage AI tools, accelerators, and digital agents to improve solution delivery and engineering productivity.
• Build reusable assets, playbooks, and frameworks that can be applied across engagements.
• Mentor and guide delivery team members through structured documentation and knowledge-sharing practices.

In this role, success is measured by:

• Client outcomes delivered and validated
• Speed from problem definition to working solution
• Adoption and production readiness of deployed solutions
• Quality of architecture and engineering decisions
• Effectiveness of stakeholder engagement and communication
• Successful knowledge transfer and client enablement

• 10–15 years of experience designing, building, and deploying software, data, analytics, or AI solutions.
• Demonstrated ownership of production systems and business-critical deliverables.
• Experience operating in client-facing or highly collaborative environments.

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