Forward deployed Engineer - Product

This role is a hands-on, customer-facing position focused on transforming complex customer workflows into production-ready AI solutions. You will collaborate closely with customers to understand their actual processes, translate these into AI agent specifications, prototype and deploy solutions, and drive successful adoption. Additionally, you will identify repeatable customer needs and product opportunities, contributing to the evolution of the platform roadmap.

Key Responsibilities

Workflow Mapping and Prioritization: Work directly with frontline users such as dispatchers, analysts, and operations leads to map workflows as they truly operate, including undocumented steps. Evaluate and prioritize workflows based on value, data readiness, and risk, focusing efforts on those that deliver measurable impact.

Agent Specification and Prototyping: Define detailed agent specifications covering inputs, data retrieval, tools, output contracts, escalation paths, and confidence thresholds. Build initial prototypes yourself, including prompts and context, and demonstrate working solutions to customers.

Collaboration and Handover: Provide clear specifications and evaluation datasets to Platform Engineering and remain engaged through production deployment. Collaborate closely with Applied AI to set and maintain quality standards, ensuring accuracy and coverage meet agreed thresholds.

Sprint Management and Adoption: Lead sprint cadences with customer product owners, delivering working software monthly. Own the adoption process through training, enablement, and workflow change management to replace legacy processes effectively.

Outcome Measurement and Product Feedback: Instrument and measure solution outcomes, presenting defensible results to customer executives at key milestones. Translate client-specific solutions into platform capabilities by writing clear product requirements.

Customer Engagement: Conduct discovery sessions with senior stakeholders and frontline users, reconciling differing perspectives. Advocate for the customer internally and maintain honesty about what should or should not be built. Support commercial discussions with technical insight without becoming the primary demo presenter.

Product Ownership: Convert business problems into product decisions rather than feature lists. Maintain and defend engagement-specific backlogs in alignment with the broader platform roadmap. Write clear specifications for engineers and concise briefs for executives. Define and instrument success metrics prior to shipping.

Technical Design and AI Expertise: Design AI agent workflows including retrieval strategies, tool integrations, structured outputs, and human-in-the-loop checkpoints. Treat prompts and context as versioned engineering artifacts. Build golden datasets for evaluation and set confidence gates and escalation policies. Map and assess data sources, schemas, quality, and permissions. Scope integrations with real APIs, understanding authentication and rate limits. Prototype using AI coding tools, SQL, and Python. Consider cost, latency, and failure modes as product decisions.

Cross-functional Collaboration: Partner closely with Platform Engineering, Applied AI, Product & Design, Go-to-Market, and customer teams. Respect the client product owner’s design authority and work through them.

Required Qualifications

- 0–3 years of experience, including new graduates, with demonstrated ability to deliver real products, tools, or systems used by others.
- Hands-on experience building with large language models (LLMs), beyond just usage.
- Proficiency with data and systems: ability to write SQL, read API documentation, and understand data flows or the capacity to learn quickly.
- Strong written communication skills capable of explaining technical concepts to non-technical stakeholders and business constraints to engineers.
- Proactive approach to discovery: engaging users and understanding workflows without waiting for direction.
- Degree in engineering, computer science, business, economics, or a related field, or an equivalent portfolio demonstrating relevant skills.

Preferred Qualifications

- 1–3 years in product, solutions engineering, technical consulting, implementation, data analysis, or software engineering within a B2B software environment.
- Experience building and shipping AI agents, retrieval-augmented generation (RAG) systems, or LLM workflows that have been used by real customers.
- Customer-facing experience in roles such as solutions, support, consulting, sales engineering, or account management.
- Background in startup or early-stage companies where processes were created from scratch.
- Familiarity with operationally intensive industries such as infrastructure, telecom, energy, logistics, financial services, or fund operations.
- Knowledge of verticals like institutional capital, digital infrastructure, enterprise back office, or public sector.
- Comfortable working across multiple time zones including MENA, Europe, Africa, or Asia.

Technical Skills

- SQL for data querying and analysis.
- API integrations including REST, authentication, webhooks, and rate limiting.
- Data modeling covering entities, quality, lineage, and permissions.
- Prototyping with AI coding tools and agent builders.
- Basic Python proficiency for reading and modifying scripts.
- Systems literacy regarding cost, fragility, and scalability.

AI Skills

- Understanding of LLM capabilities and failure modes.
- Expertise in retrieval and context engineering, agent orchestration, evaluation methods, confidence gating, escalation design, audit trails, and handling of sensitive data (PII).
- Awareness of cost and latency as critical design constraints.

Product and Customer-Facing Skills

- Strong discovery skills to identify real problems.
- Ability to decompose complex workflows into actionable specifications.
- Prioritization based on solid arguments.
- Clear writing for both engineers and executives.
- Instrumentation of metrics before shipping.
- Credibility in boardrooms and control rooms.
- Facilitation skills to drive decisions despite disagreements.
- Change management expertise to ensure adoption.
- Honesty and transparency under pressure.
- Clear written communication across time zones.

The ideal candidate is early in their career but highly driven, curious, and self-starting. Whether your background is in engineering, consulting, or AI development, you thrive on building solutions that matter and prefer hands-on engagement over passive observation. You will be supported by a senior lead initially and expected to grow into ownership quickly. The team is hiring two individuals with complementary strengths—one focused on discovery and business cases, the other on prototyping and building. Candidates are encouraged to express their preferred focus area.