Forward Deployed Engineer – Agentic AI

Tooploox is seeking a Forward Deployed Engineer to work on GenAI, agentic AI, and AI-enabled workflow transformation initiatives. The role involves working directly with clients and stakeholders to design and deliver production-grade AI solutions integrating LLMs, agentic frameworks, enterprise data, and business workflows.

• 8+ years of IT experience including software design and engineering.
• 2+ years hands-on experience architecting or building GenAI or agentic AI systems using LLM ecosystems like OpenAI, Anthropic, Gemini, Azure AI, or AWS Bedrock.
• Strong understanding of LLM orchestration, retrieval-augmented generation, vector databases, prompt engineering, and tool-calling patterns.
• Experience with 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 their AI/ML service offerings.
• Experience leading technical discussions with engineering and non-technical stakeholders in presales, discovery, or early delivery.
• Strong 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.

Nice to have:

• Prior experience as a Forward Deployed Engineer, Field Engineer, staff engineer, solution architect, or technical product lead.
• Experience with traditional AI/ML systems including model training, MLOps, data pipelines, or feature stores.
• Familiarity with frameworks for agentic or multi-component AI pipelines.
• Exposure to Responsible AI, data privacy, and governance frameworks.
• Hands-on experience with Databricks or Snowflake.
• Experience creating reusable solution blueprints, evaluation frameworks, or technical accelerators.
• Industry-recognized cloud and AI certifications from Anthropic, AWS, Azure, or Google.

• Lead discovery and solution shaping for GenAI / Agentic AI initiatives by working with client stakeholders, users, and technical teams.
• Drive early-stage opportunities including prototyping, defining 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 quickly prioritizing speed and impact.
• Evaluate and select AI frameworks, platforms, and tools like LLMs, vector databases, orchestration frameworks, cloud AI services, and agentic tooling.
• Present and explain complex AI, architecture, and delivery concepts to business and technical stakeholders.
• Support delivery teams through MVP and first production release.
• Define evaluation criteria for AI quality and business impact including accuracy, groundedness, latency, cost, adoption, and workflow effectiveness.
• Ensure solutions adhere to security, compliance, Responsible AI, observability, and production-readiness principles.
• Convert field learnings into reusable solution assets including blueprints, evaluation frameworks, and service accelerators.