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Principal Forward Deployed Engineer, Enterprise AI Productivity
Analog Devices. Partner directly with business leaders to identify productivity bottlenecks and growth opportunities .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying AI-enabled business solutions, leveraging Large Language Models and cloud-native architectures to drive measurable outcomes. Proficient in establishing evaluation frameworks and guiding stakeholders on AI governance and responsible practices.
Highest-signal resume keywords
AI Solution DesignLarge Language Models (LLMs)Cloud-Native ArchitecturesAI GovernancePrototyping and Validation
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringAI DevelopmentData Pipeline EngineeringMicroservicesDistributed SystemsWorkflow AutomationEvaluation FrameworksPerformance MetricsMulti-Agent SystemsKnowledge Graphs
Soft Skills
Strong CommunicationStorytellingExecutive Presentation Skills
Tools & Technologies
Microsoft CoPilot StudioAWS BedrockVector Database TechnologiesAI Observability Platforms
Industry Keywords
Responsible AIAI GovernanceEnterprise IntegrationsProduct AnalyticsExperimentation
Tech Stack
Tools & technologiesAWSCloudDistributed SystemsMicroservices
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 10+ years of engineering experience delivering complex software, data, and AI solutions in enterprise environments
- 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
- 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 Bedrock, and vector database technologies
- Experience building reusable platform capabilities, SDKs, shared services, and architectural patterns
- Knowledge of Responsible AI, AI governance, security, and compliance requirements
- Experience with product analytics, telemetry, experimentation, and AI observability platforms
- Background spanning software, data, AI/ML, cloud infrastructure, and platform engineering
- Applicants other than US Citizens, US Permanent Residents, and protected individuals may have to undergo an export licensing review process for access to technical data
Benefits
Comp & perks- Discretionary performance-based bonus based on personal and company factors
- Medical coverage
- Vision coverage
- Dental coverage
- 401k
- Paid vacation
- Paid holidays
- Sick time
- Other benefits