Principal Forward Deployed Engineer, Enterprise AI Productivity

Role Overview

We are seeking a Principal Forward Deployed Engineer to partner directly with business organizations and accelerate the adoption of Enterprise AI across Analog Devices.

This role sits at the intersection of product strategy, AI engineering, and business transformation. You will work closely with stakeholders to discover high-value opportunities, rapidly prototype AI-driven solutions, and evolve successful pilots into scalable enterprise platforms.

Unlike traditional engineering roles, you will operate as both a technical leader and trusted advisor, embedding with business teams to understand workflows, uncover inefficiencies, and drive measurable productivity improvements through AI and agentic systems.

Key Responsibilities

• Partner directly with business leaders to identify productivity bottlenecks and growth opportunities.

• Lead discovery workshops and translate ambiguous business challenges into AI solution roadmaps.

• Design, prototype, and deploy Enterprise AI assistants, copilots, and agentic workflows.

• Build proof-of-concepts and rapidly validate business value.

• Collaborate with platform teams to productize successful solutions using shared enterprise platforms.

• Define evaluation frameworks, KPIs, and success metrics for AI initiatives.

• Guide stakeholders on AI adoption, operationalization, governance, and responsible AI practices.

• Drive reusable patterns across AI productivity, knowledge management, customer support, engineering effectiveness, and enterprise operations.

Required Qualifications

• 10+ years of engineering experience delivering complex software, data, and AI solutions in enterprise environments.

• Demonstrated experience designing, building, and deploying AI-enabled business solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), semantic search, and agentic workflows.

• Strong software engineering background spanning cloud-native architectures, APIs, microservices, distributed systems, data pipelines, and enterprise integrations.

• Experience developing AI copilots, assistants, workflow automation, and productivity solutions that drive measurable business outcomes.

• Experience establishing evaluation frameworks, observability, experimentation, and performance metrics for AI systems.

• Ability to rapidly prototype solutions, validate business value, and scale successful pilots into production-grade platforms.

• Experience working directly with business stakeholders to translate ambiguous challenges into technical solutions and strategic roadmaps.

• Strong communication, storytelling, and executive presentation skills.

Preferred Qualifications

• Experience with multi-agent systems, agent orchestration, MCP-based integrations, knowledge graphs, and enterprise search.

• Hands-on experience with modern AI platforms and cloud ecosystems including Microsoft CoPilot Studio, AWS Bedrockand vector database technologies.

• Experience building reusable platform capabilities, SDKs, shared services, and architectural patterns that accelerate enterprise-wide adoption.

• Knowledge of Responsible AI, AI governance, security, and compliance requirements.

• Experience with product analytics, telemetry, experimentation, and AI observability platforms.

• Background spanning multiple engineering disciplines including software, data, AI/ML, cloud infrastructure, and platform engineering.