Forward Deployed Engineer – Agentic AI

Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes.

Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery- from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively.

We are looking for a Forward Deployed Engineer to work directly with clients on high ambiguity GenAI, agentic AI and AI-enabled workflow transformation initiatives . This role is designed for someone who can operate at the intersection of customer discovery, hands-on engineering, solution architecture, early delivery and production adoption.

You will work closely with client stakeholders and users to uncover the real operational problem, build thin end-to-end solutions with real systems and data, validate feasibility, shape the delivery path and stay involved through MVP or first production release to assure alignment with expected outcome.

Your mission is to turn ambiguous customer problems into validated, production-grade AI solutions.

You will help Solvd move from “we can build this” to “we have proven this works in the customer’s real operating environment.” You will bridge presales, discovery, prototyping and delivery, while converting field learnings into solution blueprints and service accelerators.

Your Responsibilities

• Lead discovery and solution shaping for GenAI / Agentic AI initiatives, working directly with client stakeholders, users and technical teams to understand workflows, systems, data and business constraints.
• Drive early-stage opportunities partnering with account executives, product analysts and technology SMEs to prototype, define scope, implementation roadmap and effort estimates.
• Translate ambiguous business problems into validated AI solution designs covering model strategy, data access, orchestration, tool use, integration patterns and production constraints.
• Build proof-of-concepts fast, prioritizing speed and impact over perfect design, technical spikes to validate architectural assumptions using real or representative systems and data.
• Evaluate and select appropriate AI frameworks, platforms and tools, including LLMs, vector databases, orchestration frameworks, cloud AI services and agentic tooling.
• Present, defend and explain complex AI, architecture and delivery concepts in simple, practical terms for both business and technical stakeholders.
• Stay involved through MVP or first production release to preserve context, support delivery teams and validate that the solution works in the customer’s operating environment.
• Define evaluation criteria for AI quality and business impact, including accuracy, groundedness, tool-call correctness, latency, cost, adoption and workflow effectiveness.
• Ensure proposed solutions adhere to security, compliance, Responsible AI, observability and production-readiness principles.
• Convert field learnings into reusable Solvd assets, including solution blueprints, evaluation frameworks and service accelerators.

Our Requirements

• 8+ years of experience in IT, including strong experience in software design and engineering.
• 2+ years of hands-on experience architecting or building GenAI or agentic AI systems using modern LLM ecosystems, such as OpenAI, Anthropic, Gemini, Azure AI or AWS Bedrock.
• Experience supporting presales solutioning, discovery, prototyping or early delivery for AI engagements.
• Strong understanding of LLM orchestration, retrieval-augmented generation, vector databases, prompt engineering and tool-calling patterns.
• Understanding of cost modeling for AI workloads, including token usage, inference scaling and hosting models.
• Proficiency with at least one major cloud platform, such as AWS, Azure or GCP, and its AI/ML service offerings.
• Demonstrated experience leading technical discussions with both engineering and non-technical stakeholders in presales, discovery or early delivery phases.
• Strong command of software engineering fundamentals, API design, integration patterns and production-readiness practices.
• Knowledge of modern software delivery practices, including CI/CD, containerization, observability and DevSecOps.
• Excellent communication, presentation, and documentation skills, with the