Forward Deployed Engineer

Role Summary:

HCLSoftware is seeking a Domain and Product Forward Deployed Engineer (FDE) to join the

Incubate Delivery function. This role sits within the build pool and is responsible for customising

and configuring Incubate solutions to deliver the specific business outcomes each customer

engagement requires.

The Domain and Product FDE acts on behalf of the client. They take the requirements and detailed design produced by the Value Owner and Context and Data Strategist and turn them into working solutions inside the product, designing workflows, configuring orchestrations, building workbenches, and implementing process-led use cases using deep product fluency and domain understanding.

This is not a core product development role. The Incubate product and solution teams own the

architecture, engineering, and roadmap of the core products. This role makes those products work in the customer’s environment, configuring, extending, and customizing them to deliver the

outcomes the engagement has been designed to achieve.

In traditional delivery, this would be recognized as a Product Specialist or Domain SME. In AI-

centred delivery, the distinction matters more. Solutions built on AI, orchestration, and agentic capabilities need people who understand both the product and the business domain well enough to configure intelligently without defaulting to unnecessary custom development, and without losing sight of what the customer is actually trying to achieve.

The role requires the judgement to know when to configure versus when to customize, when to

use product capability as intended versus when to extend it, and when to push back on a requirement that would be better served by a different approach. That judgement comes from

combining product knowledge with practical domain understanding.

Key Responsibilities

1. Solution Configuration and Build

▪ Design and configure solutions within Incubate products to meet the specific

requirements of each customer engagement.

▪ Build workflows, orchestrations, workbenches, agents, and process-led use cases using the

product’s native capabilities and tooling.

▪ Make informed decisions about when to use standard product configuration, when to

extend or customise, and when to escalate where a requirement may be better addressed

through a different approach.

▪ Ensure that configured solutions are robust, maintainable, and aligned to the product’s

intended architecture and design patterns.

▪ Work iteratively, delivering incremental capability that can be reviewed, validated, and

refined through the engagement lifecycle.

▪ Design and configure prompt templates, agent personas, and behavioral parameters that

control how AI agents interact with users, data, and business processes within each use

case.

▪ Implement business guardrails and constraints that keep agent behavior aligned to the

customer's expectations, regulatory context, and risk appetite, including tone, scope

boundaries, escalation triggers, and response limitations.

2. Domain Expertise and Product Fluency

▪ Bring practical understanding of the business domain to inform how solutions are

designed and configured, ensuring they reflect how the customer’s processes, decisions,

and workflows actually operate.

▪ Maintain deep fluency in Incubate product capabilities, tooling, and configuration options,

staying current as products evolve.

▪ Use domain and product knowledge together to identify the most effective solution

approach for each use case, avoiding over-engineering and unnecessary complexity.

▪ Advise the Context and Data Strategist and Value Owner where requirements may benefit

from adjustment based on product capability or domain insight.

▪ Establish and maintain SME feedback loops working with customer subject matter experts

to review agent behaviour, validate output quality, and iteratively refine prompt templates

and behavioural configuration based on real-world performance.

3. Working from Requirements and Detailed Design

▪ Take documented requirements and detailed design from the Context and Data Strategist

as the primary input for build work.

▪ Seek clarification from the Context and Data Strategist where specifications are ambiguous, incomplete, or where product constraints create a gap between what is specified and what can be delivered.

▪ Ensure traceability between documented requirements and what is actually built, so that QA and validation activities have a clear baseline.

▪ Flag risks, constraints, and dependencies back to the delivery team early, particularly where product limitations or data readiness issues may affect the planned approach.

4. Collaboration and Delivery Integration

▪ Work as part of the integrated delivery team, collaborating closely with AI Orchestration

and Engineering colleagues, the Context and Data Strategist, and the Quality and Compliance team.

▪ Participate in delivery ceremonies, technical discussions, and review sessions as needed.

▪ Support solution walkthroughs and demonstrations where product and domain expertise is

required, without owning customer communication directly.

▪ Coordinate with other Domain and Product FDEs where multiple use cases or workstreams

are running in parallel within an engagement.

5. Quality, Testing, and Handover

▪ Ensure that configured solutions are built to a standard that supports effective testing,

validation, and acceptance.

▪ Support the Quality and Compliance team in validating that delivered solutions meet the

documented requirements, acceptance criteria, and governance standards.

▪ Contribute to go-live readiness activities, including solution documentation, configuration

records, and handover materials for the operate phase.

▪ Support operate-phase activities where ongoing configuration, refinement, or extension of

solutions is required after initial go-live.

6. Knowledge Sharing and Reuse

▪ Contribute to the development of reusable solution patterns, configuration templates, and

domain-specific knowledge across the function.

▪ Document configuration decisions, design rationale, and lessons learned so that knowledge is retained and transferable.

▪ Share product and domain expertise with colleagues across engagements, supporting the

function’s ability to mobilize and deliver consistently.

Required Experience

• Experience in a product configuration, solution delivery, or domain specialist role within enterprise software environments.
• Practical experience designing and building solutions using enterprise software products, configuring workflows, orchestrations, business rules, or process automation.
• Demonstrable domain understanding in one or more relevant business areas, able to translate business processes and requirements into product configuration decisions.
• Experience working from documented requirements and detailed design, collaborating with business analysts or equivalent roles to clarify and refine specifications.
• Experience working as part of a multi-disciplinary delivery team, coordinating with engineering, QA, and advisory colleagues.
• Comfortable working iteratively, delivering incremental capability and adapting as requirements are refined through delivery.

Skills and Capabilities

• Product fluency: able to work confidently within enterprise software products, using native tooling and configuration capabilities to build effective solutions.
• Domain understanding: brings practical knowledge of business processes, operational workflows, and industry context that informs how solutions are designed and configured.
• Configuration judgement: knows when to use standard configuration, when to extend, and when to push back, including the judgement to shape agent behaviour through prompt design and guardrails rather than defaulting to custom development.
• Analytical thinking: able to interpret requirements, identify gaps or ambiguities, and translate specification into working solutions.
• Collaboration: works effectively as part of an integrated team, particularly alongside Context and Data Strategists, AI Orchestration engineers, and QA colleagues.
• Communication: able to articulate technical decisions, constraints, and trade-offs clearly to both technical and non-technical colleagues.
• Attention to detail: builds solutions that are robust, traceable, and aligned to documented requirements.

Desirable Experience

• Experience with HCLSoftware products or comparable enterprise software platforms.
• Experience in AI, automation, orchestration, or agentic workflow delivery, understanding how product configuration differs when AI is at the centre of the solution.
• Experience with process mining, process mapping, or operational analytics tools.
• Familiarity with integration patterns, APIs, and data connectivity in the context of enterprise solution delivery.
• Experience in environments where governance, compliance, and auditability are embedded in the delivery process.
• Experience supporting operate-phase activities: extending, optimizing, and refining solutions after initial go-live.
• Experience configuring or managing AI agents, conversational AI, or LLM-based solutions, including prompt engineering, behavioral tuning, and agent persona design.

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