Job Family:Engineering Consulting
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:- 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
