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Senior Forward Deployed Engineer – AI Application Engineer
Kyndryl. Engage directly with client executives and frontline users to translate business and operational challenges into AI adoption concepts, requirements, outcome metrics, and deployment roadmaps .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI solution architecture, technical decision-making, and client engagement, with a strong focus on delivering quality outcomes and driving AI adoption across enterprise environments. Proficient in integrating complex systems and leading multidisciplinary teams to achieve business objectives.
Highest-signal resume keywords
AI Solution ArchitectureGenerative AI ImplementationTechnical LeadershipCloud-Native ArchitectureStakeholder Engagement
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonC#Node.jsTypeScriptAI Applications DevelopmentData PlatformsSQLNoSQLRAG SolutionsAI Agents Design
Soft Skills
Client EngagementConsensus BuildingMentoringIssue ResolutionTeam Leadership
Tools & Technologies
AzureAWSGoogle CloudEnterprise Systems IntegrationPerformance Monitoring Tools
Industry Keywords
ManufacturingFinancial ServicesDistributionPublic Sector
Tech Stack
Tools & technologiesAWSAzureCloudJavaScriptNode.jsNoSQLPythonSQLTypeScript
About the role
Key responsibilities & impact- Engage directly with client executives and frontline users to translate business and operational challenges into AI adoption concepts, requirements, outcome metrics, and deployment roadmaps
- Lead architecture design and technical decision-making for enterprise solutions combining generative AI, agentic AI, RAG, cloud technologies, and data platforms
- Take end-to-end responsibility for quality and client outcomes from requirements definition through implementation, testing, production deployment, and operational improvement
- Clarify business and operational challenges, constraints, priorities, scope, and outcome metrics
- Evaluate technical options, business value, and risks, and build stakeholder consensus
- Develop AI solution architectures and deployment roadmaps
- Design, implement, and review technical integration with enterprise systems, considering performance, reliability, observability, security, and governance
- Lead multidisciplinary teams through role allocation, technical and code reviews, issue resolution, and mentoring
- Turn engagement insights into reusable assets, solution patterns, code libraries, and delivery playbooks
- Drive new business opportunities and expand the AI business
Requirements
What you’ll need- Professional experience in software design and development using one or more technologies such as Python, C#, Node.js, or TypeScript
- Experience designing and implementing AI applications or AI solutions
- Experience implementing generative AI or agentic AI and leading production deployment and operations
- Experience as a Technical Lead, setting technical direction, conducting design and code reviews, resolving issues, and developing team members
- Experience engaging directly with client executives and frontline users to translate business challenges into technical solutions and execution plans
- Experience engaging multiple stakeholders to lead critical technical decision-making and build consensus
- Experience taking ownership of major client engagements or technical domains and independently leading solution design, production deployment, and continuous improvement
- Experience integrating solutions across multiple technical domains and development teams under complex constraints, driving delivery with responsibility for quality and client outcomes
- Preferred: Experience leading client proposals, requirements definition, and consensus-building with stakeholders, including senior executives
- Preferred: Experience designing and implementing cloud-native architectures using Azure, AWS, or Google Cloud
- Preferred: Experience designing and implementing data platforms, including data pipelines and SQL/NoSQL databases
- Preferred: Experience designing and implementing AI agents or multi-agent systems
- Preferred: Experience designing, implementing, evaluating, and improving RAG solutions
- Preferred: Experience with AI system performance, observability, guardrails, Policy as Code, security, and data protection
- Preferred: Experience designing, implementing, and integrating AI solutions that connect with enterprise systems
- Preferred: Experience collaborating with global teams
- Preferred: Experience creating and deploying reusable assets, frameworks, code libraries, and best practices
- Preferred: Business domain knowledge or experience supporting clients in manufacturing, financial services, distribution, or the public sector
Benefits
Comp & perks- Flexible, supportive environment
- Well-being prioritized
- Hands-on experience
- Learning opportunities
- Opportunities to certify in all four major platforms
- Hybrid-friendly culture
- Be Well programs supporting financial, mental, physical, and social health
- Personalized development goals
- Continuous feedback
- Certifications with Microsoft, Google, and Amazon
- Coaching and hands-on experiences
- Cutting-edge learning opportunities
- Career path and development tools