Forward Deployed Engineer-AI/ML

Forward Deployed Engineers are the technical bridge between Aivar's accelerators and our customers' hardest problems. You will embed with strategic enterprise customers to scope, design, build, and ship Generative AI and agentic systems into production — and feed everything you learn back into our product roadmap. This is not sales engineering or traditional consulting. You will write code, design systems, and own outcomes end-to-end — operating with high autonomy and representing Aivar at the most senior levels in customer environments. Think hands-on AI startup CTO inside the customer's organization, with Aivar's accelerators, AWS partnership, and engineering bench behind you.

What You'll Do

 Embed with customers. Work directly with engineering, product, and business teams to understand workflows, data, and the outcomes they need.  Translate ambiguity into design. Decompose business problems into AI and agentic system designs grounded in evals, latency budgets, and cost envelopes.  Own the technical narrative. Run architecture reviews and workshops with C-suite, IT, and security stakeholders.  Architect on AWS. Build production systems on Bedrock, SageMaker, Lambda, and EKS, using Aivar's accelerators as the foundation.  Build agentic systems. Develop LLM workflows — prompt engineering, RAG, tool use, multiagent orchestration, evaluation harnesses, and guardrails.  Integrate deeply. Connect with customer systems of record — ERPs, data warehouses, CRMs, contact-center platforms, and legacy APIs.  Ship to production. Take systems from prototype to hardened deployment — observability, SLOs, cost optimization, security reviews, and runbooks.  Drive adoption. Define success metrics with the customer, instrument systems to measure them, and iterate until the numbers move.  Enable customer teams. Lead change management and training so customers can extend what you build.  Feed the product. Codify repeatable patterns into the accelerator roadmap and partner with Product and Engineering on what becomes platform vs. bespoke.

What You'll Bring

 4+ years of software engineering experience, including 2+ years in customer-facing or production-deployment roles (FDE, Solutions Engineer, Applied AI Engineer, or technical founder).  Strong coding fluency in Python and at least one of TypeScript/JavaScript, Java, or Go. You ship production code.  Hands-on production experience with LLMs — prompt engineering, RAG, agent design, evaluation frameworks, and scaled deployment.  Working knowledge of AWS for AI workloads — Bedrock, Lambda, S3, IAM, ECS/EKS, and at least one data service (RDS, DynamoDB, or OpenSearch).  Solid ML foundations — evaluation methodology, problem decomposition, and reasoning about model behavior in production.  Experience integrating across enterprise systems — REST/GraphQL, event-driven architectures, and at least one of: ERP, data warehouse, CRM, or contact-center platforms.  Strong written and verbal communication. You move comfortably between a CTO working session and a platform engineering code review.

Comfort with ambiguity, ownership of outcomes, and a bias to ship.