AI Engineer

Job Family:

Software Development & Support

Travel Required:

Up to 10%

Clearance Required:

None

What You Will Do:

• Build, test, and deploy AI applications and services, translating solution designs and reference architectures into working, demo-ready components.
• Implement data and ML pipelines (ingest, transform, feature stores, vector indexes) and wire up retrieval-augmented generation (RAG) and agentic workflows.
• Package and serve models (LLMs and traditional ML) via APIs and microservices using containers and orchestration (e.g., Docker, Kubernetes).
• Stand up and maintain cloud resources and AI platforms (AWS, Azure, GCP; Palantir; Databricks), including CI/CD, IaC (e.g., Terraform), secrets, and observability.
• Integrate AI capabilities (prompt orchestration, tool/function calling, embeddings, fine-tuning) into applications and services.
• Collaborate with data scientists, platform engineers, and product teams to iterate on use cases, deliver POCs/MVPs, and harden them for scale.
• Contribute to demos, technical documentation, and solution content for proposals and pitch materials.
• Follow responsible AI practices and security/compliance requirements across commercial and public sector environments.

What You Will Need:

• Bachelor's degree is required.
• Minimum Four (4) years of experience in software, data, or ML engineering, including building and operating cloud-native services or Master's degree and Minimum TWO (2) years of experience
• Minimum ONE (1) year of hands-on experience with Generative AI and/or agentic patterns (e.g., RAG, function/tool calling, prompt orchestration).
• Proficiency with at least one major cloud (AWS, Azure, or GCP) and modern DevOps practices (Git, CI/CD, containerization, infrastructure as code).
• Strong programming skills in Python and/or TypeScript/JavaScript; comfort working with APIs, SDKs, and common data formats.
• Familiarity with vector databases and embeddings and LLM application frameworks.
• Ability to troubleshoot production systems (logs, metrics, traces), write clear documentation/runbooks, and collaborate in cross-functional teams.
• Growth mindset with interest in expanding into broader architecture responsibilities over time.

What Would Be Nice To Have:

• Ability to obtain and maintain a Federal or DoD SECRET security clearance; active clearance preferred.
• Certifications in cloud architecture, DevOps, or AI/ML (e.g., AWS/Azure/GCP, Databricks, Kubernetes).
• Experience contributing to client-facing engineering in consulting or product environments.
• Master's degree

The annual salary range for this position is $98,000.00-$163, Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs.

What We Offer:

Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace.

Benefits include:

• Medical, Rx, Dental & Vision Insurance
• Personal and Family Sick Time & Company Paid Holidays
• Parental Leave
• 401(k) Retirement Plan
• Group Term Life and Travel Assistance
• Voluntary Life and AD&D Insurance
• Health Savings