Forward Deployed Engineer

Forward Deployed Engineer

The Forward Deployed Engineer (FDE) is a senior, customer-facing practitioner who connects customer needs, measurable business outcomes, and technology solutions. Working directly within customer environments, the FDE partners with business and technical stakeholders to understand complex challenges, reduce ambiguity, make opportunities tangible, and establish a credible path from idea to production value. The FDE combines depth in a relevant specialist discipline with broad knowledge of company and partner platforms, products, accelerators, and reusable assets. They apply domain context, technical judgement, and commercial awareness to identify high-impact opportunities and determine the most appropriate route to the customer outcome, including bespoke AI delivery, product capabilities, platform or infrastructure services, and reuse of existing assets. The FDE acts as the persistent outcome thread between customer stakeholders and internal engineering, product, architecture, delivery, and operations teams. They shape validated opportunities into delivery-ready work, remain connected through implementation and adoption, and use customer feedback and production evidence to guide improvement without replacing the accountable production delivery or managed service teams. Combining domain understanding, technical credibility, strong client emotional intelligence, and outcome leadership, the FDE operates independently in ambiguous enterprise environments and is trusted to lead complex customer engagements. The role requires hands-on problem solving, sound judgement, effective stakeholder influence, and the ability to orchestrate the right capabilities while maintaining focus on measurable customer value and scalable delivery.

Key Responsibilities:

• Partner with customers and stakeholders to understand business objectives, workflow challenges, desired outcomes, and the measures that will demonstrate success.
• Lead discovery, assessment, and solution-shaping activities that translate ambiguous business needs into clear, prioritised opportunities.
• Establish outcome hypotheses, success measures, key assumptions, and customer ownership before recommending material investment or progression.
• Create or direct rapid prototypes, proof points, experiments, and demonstrations that test the assumptions most critical to value and feasibility.
• Assess solution feasibility across AI, data, integration, architecture, security, privacy, Responsible AI, operational readiness, and cost considerations.
• Shape validated opportunities into production-ready work, including target workflow, architecture direction, prioritised backlog, dependencies, acceptance direction, estimates, and mobilisation requirements.
• Build trusted relationships with technical, business, and senior stakeholders, providing clear guidance and constructive challenge throughout customer engagements.
• Collaborate across engineering, architecture, product, delivery, operations, industry, transformation, and account teams to orchestrate the capabilities required for successful outcomes.
• Analyze and resolve complex business, technical, and operational challenges using sound judgement, evidence, and structured problem-solving.
• Identify high-value use cases by combining domain context, stakeholder insight, technology capability, feasibility, and measurable business impact.
• Determine the most appropriate delivery route, including AI Studio, company products, AI Factory, transformation services, partner capabilities, reuse, further validation, or stop.
• Maintain the outcome thread as work moves into delivery by validating major decisions, assumptions, user feedback, adoption needs, and continued alignment to the intended value.
• Capture field feedback, implementation learning, defects, feature requests, customer signals, and reusable patterns from customer engagements.
• Contribute to internal IP, accelerators, reference architectures, implementation playbooks, reusable assets, and continuous improvement of the Forward Deployed and AI Studio methods.
• Provide guidance, mentoring, and knowledge sharing to FDE Candidates and delivery practitioners to strengthen capability and successful outcomes.

Role may require working at customer sites, company offices, or hybrid delivery locations depending on engagement needs.

Knowledge and Attributes:

• Strong domain awareness with the ability to understand customer workflows, value drivers, operating constraints, industry context, and relevant success measures.
• Strong technical credibility across enterprise solution architecture, engineering practices, data, integration, cloud platforms, and production technology delivery.
• Applied understanding of artificial intelligence, generative AI, agentic systems, RAG, automation, model and tool integration, and emerging AI technologies.
• Understanding of production AI considerations including evaluation, security, privacy, Responsible AI, observability, AgentOps, FinOps, resilience, and operational readiness.
• Strong client emotional intelligence, consulting, stakeholder management, facilitation, and communication skills, with the ability to build trust quickly in senior customer environments.
• Strong analytical, problem-solving, critical-thinking, experimentation, and evidence-based decision-making capabilities.
• Deep working expertise in at least one relevant specialist area such as AI engineering, architecture, industry, transformation, product, data, or AI infrastructure.
• Broad knowledge of relevant company and partner platforms, products, accelerators, implementation methods, and reusable assets, and when to apply them.
• Ability to learn and apply domain context quickly, including processes, terminology, regulations, data flows, user roles, constraints, and business metrics.
• Commercial awareness to connect technical choices with business value, risk, cost, time to value, adoption, and the appropriate delivery model.
• Strong outcome leadership, including the ability to define measurable outcomes, surface assumptions, prioritise evidence, and drive Build, Iterate, Route, or Stop decisions.
• Strong reuse and product-feedback mindset, including the ability to distinguish customer-specific needs from patterns and improvements that should be scaled.
• Ability to communicate complex concepts clearly with domain, business, executive, engineering, architecture, and operational stakeholders using the appropriate level of detail.
• Ability to work independently, manage ambiguity, challenge constructively, and balance business, technical, commercial, and operational priorities.
• Ability to influence technical and non-technical stakeholders across multiple organizational levels without relying on formal authority.
• Strong collaboration, relationship-building, mentoring, and knowledge-sharing skills, with a bias toward creating customer and practice capability rather than individual dependency.

Required Qualifications and Certifications:

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, Business Technology, or a related discipline, or equivalent combination of education and relevant professional experience.
• Relevant industry certifications in cloud technologies, solution architecture, data, artificial intelligence, cybersecurity, agile delivery, industry domains, or related disciplines are beneficial.
• Certifications support but do not replace demonstrated FDE capability and accreditation.

Required Experience:

• Typically 8+ years of relevant experience in software or AI engineering, solution architecture, consulting, customer engineering, product engineering, industry transformation, technology delivery, or related disciplines, with equivalent demonstrated depth considered.
• Significant experience working directly with enterprise customers and building credibility with business, technical, and senior stakeholders.
• Experience independently leading discovery, problem framing, solution shaping, or complex customer workstreams in ambiguous environments.
• Experience creating or directing prototypes, proof points, technical experiments, or working solutions to validate customer and technology assumptions.
• Experience shaping and delivering enterprise technology solutions involving architecture, data, integration, security, deployment, and production constraints.
• Experience applying domain or functional context to customer workflows, constraints, KPIs, value drivers, and solution decisions.
• Experience connecting technology decisions to measurable customer outcomes, adoption, business value, risk reduction, operational efficiency, or customer experience.
• Experience collaborating with product, engineering, platform, industry, transformation, delivery, and business teams to determine the right solution and delivery route.
• Experience evaluating build, buy, reuse, product, partner, and platform options pragmatically rather than defaulting to bespoke implementation.
• Experience operating within complex enterprise environments and navigating dependencies across technology, data, governance, operations, and customer organizations.
• Experience operating independently, exercising sound judgement, influencing decisions, and maintaining momentum through uncertainty and changing priorities.
• Experience capturing reusable patterns, field feedback, lessons learned, methodologies, accelerators, or other assets that improve future delivery.
• Experience providing guidance, mentoring, peer review, or knowledge sharing to colleagues and developing practitioners.

NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role will depend on the nature of the role offered and will either be [$155,700 - $259,500], or [$80-$100] if the role is hired as a temporary position. Actual compensation will depend on a number of factors, including the candidate's relevant experience, technical skills, and other qualifications. This position may also be eligible for incentive compensation based on individual and/or company performance. If the position offered in temporary, the position will not be eligible for incentive compensation. This position is eligible