Forward Deployed Engineer - Architect

Jade Global • San Jose, CA

21h

About The Position

The Forward Deployed Engineer - Architect leads customer discovery and translates customer priorities into practical AI and software solutions. The role maps workflows, identifies bottlenecks, assesses data and system readiness, defines measurable success criteria, and determines where AI, conventional software, or human review is appropriate.

The engineer builds production-quality AI applications, agents, and supporting services, including APIs, retrieval pipelines, integrations, orchestration logic, and user interfaces. The role connects solutions to enterprise applications and data sources, establishes evaluation and acceptance criteria, and owns production readiness in partnership with customers and Jade teams. Responsibilities also include guiding delivery engineers while coding and reviewing code, measuring adoption and business impact, and contributing reusable components and feedback to Jade Orbit and Jade's FDE delivery methods.

This position offers the opportunity to help shape Jade Global's growing AI Engineering Services business, work directly with enterprise customers, and build solutions for everyday business operations. The engineer will use Jade's engineering practices and evolving AI platforms and reusable solutions, while helping develop FDE-led delivery approaches.

Requirements

• At least 6 years of hands-on software engineering experience, including at least 2 years building LLM-powered applications or agentic systems.
• Demonstrated ownership of multiple production deployments and ability to explain personally written code, architecture decisions, failure modes, and outcomes.
• Strong Python skills, including asynchronous programming, API development, automated testing, and debugging.
• Solid grounding in SQL, data structures, distributed systems, and application design, with ability to work across backend and user-facing components.
• Deep understanding of LLM application architecture, including model selection, embeddings, context management, structured outputs, tool calling, and inference tradeoffs; ability to balance quality, latency, cost, and privacy.
• Hands-on experience engineering agents and orchestration with a framework or custom implementation, including explicit state, persisted checkpoints, retries, idempotent tool execution, human approvals, and recovery from partial failures.
• Experience building and tuning retrieval-augmented generation pipelines, including ingestion, chunking, embeddings, hybrid search, metadata filtering, reranking, and access-aware retrieval; ability to diagnose retrieval quality and grounding failures.
• Experience developing rigorous AI evaluations using representative datasets, task-level metrics, regression tests, and adversarial cases; ability to measure factual accuracy, tool-use correctness, task completion, and failure rates.
• Strong enterprise integration skills across APIs, authentication, databases, and event-driven systems, including exposing business capabilities as secure tools and implementing agent permission boundaries.
• Hands-on production deployment and operations experience on a major cloud platform, including containers, CI/CD, secrets management, tracing, monitoring, and incident diagnosis; ability to manage concurrency, rate limits, inference costs, and reliability.
• Practical experience securing AI applications against prompt injection, sensitive-data exposure, and unauthorized tool execution, including least-privilege access, audit trails, validation, and appropriate human review.
• Ability to lead technical discovery and architecture discussions with customers, turn incomplete requirements into working software, and guide distributed engineers while continuing to write and review production code.

Nice To Haves

• Previous experience as an FDE, customer engineer, hands-on technical consultant, technical founder, or solutions architect with substantial coding and deployment ownership.
• Experience with agent orchestration frameworks, Model Context Protocol integrations, LLM observability, evaluation pipelines, or model selection and fine-tuning when warranted by the use case.
• Experience building enterprise AI foundations, modernizing applications with AI, or working with open-source models and private deployment requirements.
• Delivery experience in manufacturing, high-tech, or healthcare and life sciences, and experience collaborating with distributed engineering teams.

Responsibilities

• Lead discovery with business users and technology teams; map workflows, identify bottlenecks, assess data and system readiness, and agree on problems and measurable success criteria.
• Translate customer priorities into solution designs and delivery plans, choosing appropriately between AI, conventional software, and human review.
• Build production-quality AI applications, agents, APIs, retrieval pipelines, tool integrations, orchestration logic, and user interfaces as needed.
• Integrate solutions with enterprise applications and data sources, addressing authentication, permissions, data quality, and reliable cross-system execution.
• Create evaluation datasets and acceptance criteria; test task completion, output quality, failure modes, latency, and cost, and improve solutions based on results.
• Own production readiness with customers and Jade teams by implementing access controls, auditability, monitoring, safe fallbacks, human approvals, and operational handover; troubleshoot after launch.
• Provide technical direction to the delivery team while writing and reviewing code; manage dependencies, raise risks, and explain scope, architecture, and delivery tradeoffs to customers.
• Measure adoption and business impact against an agreed baseline, turn successful patterns into reusable components, and contribute field feedback to Jade Orbit and FDE delivery methods.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed