Senior AI Engineer

• Architect and deliver end-to-end AI/ML solutions on Google Cloud using Vertex AI and Gemini/LLM services

• Develop production data pipelines with BigQuery, Dataflow, and Dataproc; integrate streaming via Pub/Sub

• Containerize and orchestrate workloads with Cloud Run and GKE

• Automate CI/CD with Cloud Build and infrastructure as code

• Implement MLOps practices including experiment tracking, evaluation, bias/robustness testing, model versioning, canary/blue-green rollouts, automated retraining, drift detection, and lineage

• Apply secure-by-design patterns aligned to NIST 800-53, RMF, and FedRAMP baselines

• Operationalize LLM/GenAI using RAG, tool-use/agents, safety filters, evaluation harnesses, and structured/unstructured data retrieval

• Partner with mission stakeholders to elicit requirements, define measurable success criteria, and deliver iterative value

• Provide technical mentorship and lead design and code reviews

• Contribute to program roadmaps and document architectures, controls, and SOPs for sustained operations

Requirements

• US citizenship with the ability to obtain successful DoW Secret security clearance required; candidates with active Secret clearance preferred

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field

• Advanced degree (Master's Degree or PhD) in AI/ML, Data Science, Computer Science, or a closely related discipline preferred but not required

• 8+ years total software development/data experience with 5+ years focused on AI/ML engineering and MLOps, including production deployments on Google Cloud (GCP)

• Experience architecting data ingestion, processing, and transformation workflows using Dataflow, Data Fusion, Dataproc, BigQuery, and Looker, integrated with Vertex AI

• Current Google Associate Cloud Engineer (GCP-ACE) or Google Professional Cloud Architect (GCP-PCA) certification, or ability to obtain within 90 days of hire

• At least one current DoW Cyber Baseline Certification, such as Security+ Intermediate or SecurityX/CASP+ Advanced, or ability to obtain within 90 days of hire

• Experience extracting data from SAP Enterprise Business Applications

• Expert Python and/or Go/TypeScript skills for AI services

• Strong knowledge of Vertex AI, BigQuery, Dataflow and/or Data Fusion, GKE/Cloud Run, Cloud Build, Cloud Storage, and Pub/Sub

• Practical experience with LLMs/GenAI, vector databases, prompt engineering, RAG patterns, and evaluation/guardrails

• Proven MLOps experience and strong data engineering fundamentals

• Ability to design for security and compliance in DoW/Federal contexts, including NIST 800-53, RMF, FedRAMP, and Zero Trust principles

• Hands-on experience with Vertex AI Agent Builder, Model Garden, embeddings/vector search, and evaluation frameworks

• Experience integrating GenAI safely within IL5 environments and familiarity with government AI platforms

Core Competencies

Demonstrates expertise in architecting and delivering AI/ML solutions on Google Cloud, with a strong focus on MLOps practices and data engineering. Proficient in implementing secure-by-design patterns and operationalizing LLM/GenAI technologies in compliance with federal standards.

Highest-signal resume keywords

• AI/ML Solution Architecture

• MLOps Implementation

• Google Cloud Platform (GCP)

• Data Engineering Fundamentals

• Security and Compliance Design

ATS Optimization Keywords

Hard Skills

• Python

• Go

• TypeScript

• Vertex AI

• BigQuery

• Dataflow

• Dataproc

• Cloud Run

• GKE

• MLOps

Soft Skills

• Technical Mentorship

• Stakeholder Collaboration

• Design Review Leadership

Certifications & Qualifications

• Google Associate Cloud Engineer (GCP-ACE)

• Google Professional Cloud Architect (GCP-PCA)

• DoW Cyber Baseline Certification

Industry Keywords

• NIST 800-53

• RMF

• FedRAMP

• Zero Trust

• IL5 Environments

Tools & Technologies

• Cloud Build

• Pub/Sub

• Data Fusion

• Looker

• Vertex AI Agent Builder

• Model Garden