Forward Deployed Engineer – Agentic AI

Accountabilities:

• • Lead discovery and solution-shaping activities for GenAI, agentic AI, and AI-enabled workflow transformation initiatives, partnering directly with client stakeholders, users, and technical teams.
  • Work alongside account executives, product analysts, and technology specialists to develop early-stage opportunities, define scope, prototype solutions, and establish implementation roadmaps and effort estimates.
  • Translate complex and ambiguous business challenges into practical AI solution architectures covering model selection, data access, orchestration, tool use, integrations, and production constraints.
  • Build rapid proof-of-concepts and technical prototypes using real or representative systems and data, prioritizing speed, learning, and measurable impact.
  • Evaluate and select appropriate AI frameworks, LLMs, vector databases, orchestration tools, cloud AI services, and agentic technologies based on customer requirements.
  • Explain and present complex AI, architecture, and delivery concepts clearly to executives, business users, product teams, and engineers.
  • Remain engaged through MVP or initial production release to preserve technical and business context, support delivery teams, and validate that solutions perform effectively in the customer's operating environment.
  • Define evaluation frameworks and success criteria covering AI quality, accuracy, groundedness, tool-call reliability, latency, cost, adoption, and workflow effectiveness.
  • Ensure solutions incorporate appropriate security, compliance, Responsible AI, observability, governance, and production-readiness practices.
  • Capture field insights and convert them into reusable technical assets, including solution blueprints, evaluation frameworks, implementation patterns, and service accelerators.

  Requirements

  • 8+ years of professional IT experience, including substantial hands-on experience in software engineering, system design, or related technical disciplines.
  • At least 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.
  • Strong software engineering background with experience designing, prototyping, integrating, and deploying systems that combine LLMs, enterprise data, AI agents, and business workflows.
  • Solid understanding of LLM orchestration, retrieval-augmented generation, vector databases, prompt engineering, tool calling, and agentic application patterns.
  • Experience selecting and applying established engineering practices alongside emerging AI capabilities to create reliable, production-ready solutions.
  • Proficiency with at least one major cloud platform, such as AWS, Azure, or GCP, including relevant AI/ML services.
  • Experience with APIs, integration architectures, software engineering fundamentals, and production-readiness practices.
  • Knowledge of modern delivery practices such as CI/CD, containerization, observability, DevSecOps, and scalable cloud deployment.
  • Understanding of AI workload economics, including token consumption, inference scaling, hosting approaches, and cost modeling.
  • Experience supporting presales solutioning, customer discovery, prototyping, or early-stage delivery for AI and technology engagements.
  • Demonstrated ability to lead technical discussions with both technical and non-technical stakeholders and translate complex concepts into compelling, actionable recommendations.
  • Strong communication, presentation, documentation, collaboration, and stakeholder-management skills.
  • Pragmatic, curious, adaptable, and highly customer-focused, with the ability to navigate ambiguity while balancing technical quality, business value, user adoption, and delivery readiness.
  • Prior experience as a Forward Deployed Engineer, Field Engineer, Staff Engineer, Solution Architect, or Technical Product Lead is a plus.
  • Familiarity with traditional AI/ML, MLOps, data pipelines, feature stores, agentic or multi-component AI frameworks, Responsible AI, data privacy, and governance is advantageous.
  • Experience with Databricks or Snowflake, reusable technical accelerators, solution blueprints, or AI evaluation frameworks is a plus.
  • Industry-recognized cloud or AI certifications from providers such as AWS, Azure, Google, or Anthropic are beneficial.

  Benefits

  • Opportunity to work on real-world GenAI and agentic AI transformation projects across multiple industries.
  • Exposure to both startup innovation and complex enterprise transformation initiatives.
  • Hands-on involvement across the full AI solution lifecycle, from customer discovery and prototyping through MVP and initial production deployment.
  • Global and collaborative working environment with opportunities to work across cultures and continents.
  • Strong emphasis on continuous learning, technical innovation, and professional growth.
  • Opportunity to develop reusable AI solution frameworks, accelerators, and delivery methodologies.
  • Inclusive environment focused on collaboration, innovation, and responsible AI practices.
  • High level of technical ownership and direct interaction with customers and senior stakeholders.
  • Opportunity to work with modern LLM ecosystems, cloud AI platforms, agentic frameworks, and enterprise data technologies.