AI Engineer (GCP / Google ADK)

AI Engineer (GCP / Google ADK)

Reston, VA Type: Full-time Min. Experience: Senior Level Opportunity

Northramp is seeking a mid to senior-level AI Engineer to design and build AI-driven capabilities for federal environments using Google ADK, Vertex AI, Gemini models, and the broader GCP ecosystem. You will focus on hands-on engineering—developing workflows, integrating services, and delivering secure, auditable AI components that meet federal standards. You'll work closely with polyglot full-stack teams, primarily Java/Angular, but also other modern frameworks, to integrate AI services into enterprise applications. As part of a scaled agile team, you'll collaborate with senior engineers and architects to implement solution patterns, maintain technical quality, and support production deployments. The role involves building AI-powered workflows, enforcing traceability and model-evaluation requirements, and producing the documentation required for federal oversight. Occasional on-site support in the Washington, D.C. area may be necessary; remote work may be approved based on client needs. The ideal candidate has strong hands-on engineering skills, experience implementing AI systems on GCP, and the ability to contribute to architectural discussions while working closely with cross-functional development teams.

Key Responsibilities

• AI Architecture & Engineering
• Build and maintain AI workflows using Google ADK, including agent definitions, tool integrations, and workflow logic.
• Implement Vertex AI / Gemini model calls, handle prompt design, manage parameters, and ensure consistent output quality.
• Develop and maintain Python or Typescript services/utilities that integrate AI workflows into existing enterprise applications.
• Implement evaluation tests for agents (prompt regression tests, scenario tests, safety checks).
• Application & System Integration
• Integrate AI features with Java backends and Angular UIs using REST APIs, shared adapters, or lightweight service endpoints.
• Build small, reusable components for partner teams (e.g., sample API code, simple SDKs, interface contracts).
• Work with full-stack developers to embed AI capabilities in user-facing features such as summaries, recommendations, or data extraction.
• Cloud & Platform Engineering
• Deploy AI workloads to Cloud Run or Cloud Functions, ensuring proper IAM, service accounts, and network restrictions.
• Use Terraform to define and manage AI-related cloud resources (service accounts, storage buckets, API configs).
• Configure logging, monitoring, and error tracking for AI workflows using Cloud Logging / Cloud Monitoring.
• Quality, Compliance & Documentation
• Deploy AI workloads to Cloud Run or Cloud Functions, ensuring proper IAM, service accounts, and network restrictions.
• Use Terraform to define and manage AI-related cloud resources (service accounts, storage buckets, API configs).
• Configure logging, monitoring, and error tracking for AI workflows using Cloud Logging / Cloud Monitoring.
• Collaboration & Communication
• Provide clear status updates and surface risks or blockers early.
• Collaborate with architects and senior engineers to refine designs and follow established solution patterns.
• Offer light mentorship or troubleshooting support for teammates adopting AI patterns.
• Communicate technical concepts in a way that is understandable to product owners, analysts, and non-technical stakeholders.

Required Qualifications

• Ability to obtain and maintain a Public Trust adjudication as required by the federal engagement.
• 3+ years of experience in software engineering, machine learning engineering, or cloud-based AI development.
• Hands-on Google ADK experience building real applications (minimum six months strongly preferred).
• Proficiency in Python or Typescript for agent logic, API development, automation, and workflow orchestration.
• Experience with GCP services such as Cloud Run, Cloud Functions, Cloud Storage, BigQuery, Pub/Sub, and IAM.
• Familiarity with ML lifecycle practices, including prompt engineering, evaluation methods, observability, and safety controls.
• Excellent communication, collaboration, and problem-solving skills, including the ability to explain complex AI concepts to non-technical audiences.

Preferred Qualifications

• Experience with Google Enterprise Agents, ACE methods, or agent-oriented application design.
• Knowledge of federal security frameworks such as NIST 800-53, FedRAMP, and Zero Trust architectural principles.
• Previous experience supporting federal modernization efforts, AI programs, or documentation-heavy environments.
• Background in designing or reviewing AI governance frameworks, model risk processes, or responsible-AI policies.

Specific Technical Skills

• Hands-on experience with Google ADK, Vertex AI, and Gemini APIs.
• Proficiency in Python or Typescript for agent logic and workflow development.
• Familiarity with REST API design, JSON schemas, and integration with backend services.
• Working knowledge of:
• Cloud Run
• Cloud Functions
• Cloud Storage
• IAM (service accounts, roles, workload identity)
• BigQuery (basic querying, logging pipelines)
• Pub/Sub (event-driven triggers, simple ingest pipelines)

Clearance

The selected applicants may be subject to a security investigation and must meet eligibility requirements for access to classified information, if required.