AI Engineer (Mid)

We are looking for an Application Architect with strong AI engineering experience to design and build intelligent, agentic applications on Google Cloud Platform. This role sits within an application engineering team and focuses on architecting AI-enabled systems using the Google Agentic Development Kit (ADK), Gemini, and Vertex AI — integrated into enterprise Java/Python backends and cloud-native microservices. You are equally comfortable defining application architecture, designing agentic workflows, writing production-quality code, and translating AI capabilities into practical, mission-aligned solutions for federal stakeholders.

This role is remote with a preference for candidates located in Virginia, Maryland, or Washington DC.

Key Responsibilities

• Architect and implement AI-enabled application systems on GCP, with a focus on agentic workflows using Google ADK and Gemini Pro.
• Design human-in-the-loop agentic systems — defining agent roles, tool use, orchestration patterns, and guardrails for responsible, auditable AI behavior.
• Integrate AI/ML capabilities (Vertex AI, Gemini APIs, embeddings, RAG) into enterprise Java and Python applications via well-designed APIs and microservices.
• Lead application-layer design decisions: data flow, context management, session handling, and state management within agentic architectures.
• Collaborate with Data Engineers (BigQuery, Dataform) and Cloud Architects to ensure AI application solutions are grounded in reliable, governed data.
• Conduct architectural reviews, define coding standards for AI-integrated applications, and mentor engineers on agentic design patterns.
• Evaluate AI use cases for feasibility, risk, and mission fit; prototype and validate approaches before committing to full builds.
• Contribute to responsible AI practices: explainability, human oversight, auditability, and alignment with federal AI governance requirements.
• Stay current on the Google AI ecosystem (Gemini, ADK, Vertex AI Agent Builder) and inform team and leadership on strategic direction.

Requirements

Required Qualifications

•  5–8 years of software or application engineering experience, with demonstrated focus on AI-integrated or intelligent application design.
• Hands-on experience with Google ADK or comparable agentic frameworks (LangGraph, LangChain, AutoGen); Google ADK strongly preferred.
• Proficiency in Python for AI/ML integration; Java experience a plus in application team context.
• Experience integrating LLM APIs (Gemini, OpenAI, or equivalent) into production application workflows.
• Solid understanding of agentic design patterns: tool use, multi-agent orchestration, retrieval-augmented generation (RAG), memory and context management.
• Experience with GCP services: Vertex AI, Cloud Run, GKE, BigQuery, Pub/Sub.
• Familiarity with REST API design, microservices architecture, and CI/CD pipelines (Harness preferred).
• Understanding of responsible AI principles: human-in-the-loop design, auditability, bias awareness, and federal AI governance.

Desired Qualifications

• Experience with Vertex AI Agent Builder, Gemini Code Assist, or Gemini CLI in a development workflow context.
• Familiarity with GCP-native data tooling: BigQuery, Dataform, Looker.
• Experience on federal or large-scale enterprise modernization programs.
• Exposure to FedRAMP/FISMA requirements and security-compliant AI deployment practices.
• Experience with DevSecOps pipelines (Checkmarx, Invicti, or equivalent SAST/DAST tooling).

Additional Information

• Successful completion of a client-required background investigation and suitability determination will be required.
• The ability to obtain and maintain a federal security clearance may be required based on engagement.
• Bachelor's degree in Computer Science, Software Engineering, or a related field; advanced degree a plus.
• Google Cloud Professional Cloud Architect or Professional Machine Learning Engineer certification preferred.
• Security+ desirable.

Benefits

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA)
• Life Insurance (Basic, Voluntary & AD&D)
• Paid Time Off (Vacation, Sick & Public Holidays)
• Family Leave (Maternity, Paternity)
• Short Term & Long Term Disability
• Training & Development
• Work From Home
• Wellness Resources
• Employee Bonus Programs