This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Forward Deployed Engineer – Agentic AI based in the United States.
This is a hands-on technical role focused on turning ambiguous business challenges into validated, production-ready GenAI and agentic AI solutions.
You will work directly with clients to understand operational workflows, systems, data, and business constraints before shaping practical AI solutions.
The role spans customer discovery, solution architecture, rapid prototyping, technical validation, and early production delivery.
You will build thin end-to-end solutions using real or representative data, helping clients move from AI concepts to measurable business outcomes.
Working across business, product, engineering, and technical stakeholders, you will translate complex AI capabilities into clear and actionable solutions.
You will also help establish reusable solution blueprints, evaluation frameworks, and accelerators that strengthen future AI engagements.
The environment is highly collaborative, fast-moving, and innovation-driven, with significant ownership and exposure to enterprise AI transformation initiatives.
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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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