AI Engineer

• 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.

• US Citizenship is required
• Bachelor's degree is required.
• Minimum THREE (3) years of experience in software, data, or ML engineering, including building and operating cloud-native services.
• 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).
• Serve as a forward deployed engineer, collaborating with data scientists, platform engineers, and product teams to rapidly iterate on solutions, deliver POCs/MVPs, and harden them for production scale.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-$163,000.00. 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
• Position may be eligible for a discretionary variable incentive bonus
• Parental Leave and Adoption Assistance
• 401(k) Retirement Plan
• Basic Life & Supplemental Life
• Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
• Short-Term & Long-Term Disability
• Student Loan PayDown
• Tuition Reimbursement, Personal Development & Learning Opportunities
• Skills Development & Certifications
• Employee Referral Program
• Corporate Sponsored Events & Community Outreach
• Emergency Back-Up Childcare Program
• Mobility Stipend

About Guidehouse

Guidehouse is an Equal Opportunity Employer-Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation.

Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco.