Location: Remote
Duration: 12+ Months Contract (Possible Extension)
About the Role
STAFFXPERT LLC is seeking a Principal Forward Deployed AI Engineer on behalf of our client. This is a high-impact opportunity for a senior AI engineer who thrives in complex production environments and is passionate about solving mission-critical AI deployment challenges.
As part of an elite AI response team, you will be deployed into enterprise customer engagements facing critical technical challenges. You will take ownership of troubleshooting, stabilizing, and optimizing AI-powered systems, ensuring successful outcomes for clients across Banking, Healthcare, Financial Services, and Retail industries.
This role requires deep expertise in AI/LLM systems, production engineering, cloud-native architectures, and enterprise client engagement.
Key Responsibilities
AI Deployment Recovery & Technical Leadership
Lead turnaround efforts for high-priority customer engagements experiencing AI platform, agent, or deployment issues.
Quickly diagnose root causes and implement remediation plans within fast-paced production environments.
Take ownership of technical delivery and establish engineering best practices across client teams.
Engage directly with senior stakeholders, architects, and executives to communicate risks, solutions, and technical strategies.
AI Agent Engineering & Optimization
Debug and optimize production AI agents built on Google Gemini, GECX, G3, and related AI frameworks.
Design deterministic fallback mechanisms to improve reliability and reduce LLM failure scenarios.
Refactor agent workflows, prompts, and orchestration layers to improve consistency and scalability.
Implement schema validation, structured output handling, guardrails, and workflow controls.
Analyze logs, tracing data, and telemetry to identify and resolve performance bottlenecks.
Software Engineering & System Integration
Refactor and enhance cloud-native microservices using Python, TypeScript/JavaScript, or Go.
Integrate AI agents with enterprise APIs, CRMs, databases, and legacy systems.
Optimize RAG pipelines, vector search architectures, and agent orchestration frameworks.
Improve observability, evaluation metrics, latency, scalability, reliability, and cost efficiency.
Required Qualifications
Software Engineering
6+ years of hands-on software engineering experience.
Strong expertise in Python, TypeScript/JavaScript, or Go.
Experience building and supporting cloud-native applications on Google Cloud Platform (Google Cloud Platform).
Background in distributed systems, APIs, and microservices architecture.
AI & Generative AI Expertise
Proven experience developing and supporting production-grade LLM applications.
Strong knowledge of RAG architectures, vector databases, and AI orchestration frameworks.
Experience with LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or similar frameworks.
Ability to troubleshoot complex AI agent failures and optimize model interactions.
LLM Reliability & Governance
Experience implementing:
Structured JSON outputs
Function/tool calling validation
Prompt engineering and workflow controls
Schema enforcement
Guardrails and safety mechanisms
Deterministic fallback architectures
Enterprise Systems Integration
Experience integrating AI solutions with enterprise applications and legacy platforms.
Background working in regulated industries such as Banking, Healthcare, Insurance, or Financial Services.
Familiarity with compliance frameworks including PCI, HIPAA, and security best practices.
Preferred Qualifications
Prior experience as a Forward Deployed Engineer, Solutions Architect, or AI Consultant at a leading AI, cloud, or consulting organization.
Experience implementing AI governance, fraud detection, compliance, and auditability solutions.
Strong background in AI observability, evaluation frameworks, telemetry, hallucination monitoring, and performance optimization.
Experience supporting enterprise AI transformations and executive-level client engagements.
Desired Traits
Strong problem-solving and troubleshooting mindset.
Comfortable working within ambiguous and complex technical environments.
Exceptional stakeholder management and communication skills.
Proven ability to perform under pressure and drive mission-critical projects to successful outcomes.
Ownership mentality with a strong focus on execution and results.
Quick learner capable of rapidly mastering new technologies and frameworks.
Training & Onboarding
Selected candidates will participate in an intensive hands-on enablement program led by Google AI subject matter experts, covering:
Google GECX & G3 Frameworks
Gemini-Based Agent Development
Deterministic AI Architecture
Advanced Debugging Techniques
Production AI Reliability & Recovery Strategies
Enterprise Account Turnaround Methodologies