AI Engineer

Job Summary

The AI Engineer supports system-specific implementations that embed AI/ML and agentic automation to accelerate metadata identification, extraction, enrichment, and documentation. This role owns the metadata harvesting plan and leads the design and implementation of AI-assisted workflows that generate validated metadata artifacts (e.g., semantic tags, data dictionary entries, and supporting documentation) using client-approved tools and human-in-the-loop steward review cycles. The AI Engineer is accountable for automated metadata harvesting and documentation, delivering automated harvesting and AI-assisted documentation outputs while operating within approved governance and security guardrails.

Key Responsibilities

• Design AI-assisted metadata harvesting & enrichment: Build AI/ML-enabled approaches to identify, extract, normalize, and enrich technical, business, and operational metadata from structured and semi-structured sources (e.g., databases, pipelines, file/document repositories) and generate semantic tags and documentation outputs.
• Implement agentic/GenAI workflows for metadata documentation: Design and implement agentic AI patterns to support autonomous or semi-autonomous metadata exploration, summarization, and documentation generation-while maintaining human validation and auditability.
• Own the metadata harvesting plan: Define scope, sequencing, cadence, source coverage, extraction methods, staging, validation, and handoffs; maintain decision logs and traceability for stewardship and governance review.
• Human-in-the-loop steward validation: Facilitate structured in-person/virtual review cycles with data stewards to validate AI-generated metadata, resolve discrepancies, and continuously improve extraction/enrichment accuracy.
• Responsible automation scoping: Identify where automation is feasible vs. where systems require manual curation; document constraints and remediation needs without attempting to "automate through" non-harvestable environments.
• Build and maintain scalable pipelines (metadata-focused): Implement and maintain scalable pipelines that integrate structured and unstructured sources for metadata extraction and enrichment; apply strong engineering discipline for reliability and repeatability.
• RAG / knowledge integration for semantic discovery: Lead work that connects harvested metadata to semantic search patterns using retrieval-augmented generation (RAG) concepts and, where applicable, knowledge graph integration to improve discoverability and semantic alignment.
• Metadata quality metrics & validation controls: Define and implement checks for completeness, accuracy, timeliness, and consistency; flag issues for remediation and support governance escalation where required.
• Technical testing & verification: Plan and execute tests to verify the metadata extraction/enrichment process works reliably across supported sources; contribute to regression coverage and repeatable validation workflows.
• Mentor and elevate engineering rigor: Mentor junior team members on agentic AI/GenAI engineering patterns, metadata quality practices, and documentation standards.

What you will need:

• Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST". Candidates with an ACTIVE SECRET CLEARANCE OR PUBLIC TRUST or SUITABILITY are preferred.
• Once onboard with Guidehouse, new hire MUST be able to OBTAIN and MAINTAIN a Federal or DoD "SECRET" security clearance.
• Bachelor's degree obtained.
• 3-5+ years of experience in AI engineering, applied ML, or data/AI solution development in enterprise environments (senior-level expectations aligned to the referenced agentic AI role).
• Strong proficiency in Python; working proficiency in SQL; familiarity with R is beneficial for statistical validation/profiling.
• Hands-on experience with Generative AI (LLMs and/or similar) and Agentic AI architectures applied to real workflows.
• Experience with RAG pipelines, and familiarity with vector databases and knowledge graphs (for semantic retrieval and metadata-driven discovery).
• Experience with AI/ML frameworks such as TensorFlow and/or PyTorch (or equivalent).
• Demonstrated ability to translate AI techniques into practical, auditable engineering outcomes and communicate clearly with both technical SMEs and non-technical stakeholders.

What Would Be Nice to Have:

• Familiarity with AI governance, ethical/responsible AI practices, and operating in compliance-driven environments.
• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related field
• Proficiency with visualization tools and interactive dashboards to communicate metadata quality, coverage, and validation results.
• Agile delivery experience (sprint-based delivery; backlog/issue tracking).
• Prior consulting experience delivering AI-enabled solutions in complex enterprise environments.
• Exposure to metadata/catalog patterns and metadata-focused engineering (harvesting, catalog population concepts, semantic discovery / lineage concepts).

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