Principal AI Engineer

Job Title: Principal AI Engineer

Location: Vienna, VA

Duration: 6 Months + Extension

Bill Rate: $67/hour

Job Type: C2C/1099 Contract

Client: To Be Discussed Later

Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Summary:
Responsibilities:

• Lead delivery of AI solutions from discovery through production, ensuring predictable execution, risk management, and measurable value realization.
• Define and socialize technical delivery plans, milestones, dependencies, and release readiness criteria; proactively surface tradeoffs and decision points.
• Translate business problems into implementable designs and backlog-ready work, maintaining alignment across engineering, security/risk, architecture, and business stakeholders.
• Architect and implement scalable AI systems, including data pipelines, model training/inference patterns, and integration into applications/services.
• Build and deploy AI solutions leveraging modern AI platforms and orchestration patterns (e.g., LLM/agent workflows, RAG, model grounding, evaluation gates, safety controls) as applicable to the use case.
• Establish and enforce strong engineering discipline: code quality, automated testing, performance tuning, observability, and operational runbooks for AI services.
• Lead by example in debugging complex issues, completing critical path implementation work, and unblocking teams through direct technical contribution.
• Develop concise, executive-ready narratives (1-pagers, readouts, and decks) that clearly communicate: problem statement, approach, progress, risks, decisions needed, and business impact.
• Present technical strategies and delivery status to senior leadership and mixed audiences, adjusting depth while preserving accuracy and decision clarity.
• Own technical "storytelling" for major milestones (architecture approvals, governance checkpoints, production readiness) with crisp visuals and artifacts.
• Define and promote reusable patterns, components, and best practices for AI engineering to accelerate delivery across teams.
• Develop and publish AI standards/best practices and participate in model lifecycle governance (e.g., model registration/curation processes, evaluation and transparency measures).
• Contribute to technology roadmaps and guidance that standardizes delivery and improves operational resilience.
• Mentor engineers, lead design and code reviews, develop communities of practice, and systematically raise AI engineering capability across delivery teams.
• Demonstrates end-to-end accountability for the strategy, architecture, standards, roadmap, adoption, and operational maturity of an assigned technical domain. Serves as the organization's recognized subject-matter authority while ensuring the domain's capabilities are reusable, measurable, governed, and effectively adopted across delivery teams.
• Complete work with minimal supervision.

Qualifications

• Bachelor's Degree in Computer Science, Statistics, Engineering or related field, or the equivalent combination of education, training and experience.
• 7-10 years of experience in AI or similar.
• Experience with modern Generative AI and agentic patterns (e.g., LLM workflows, orchestration frameworks, RAG, grounding, evaluation, safety controls).
• Experience establishing AI standards, best practices, and scalable enablement mechanisms (reference architectures, reusable components).
• Proven track record of driving and coordinating use of GenAI Code Assistants (GitHub Copilot, etc.) to drive Developer Productivity initiatives across the organization with clear value metrics.
• Hands-on experience building production grade AI agents using industry leading platforms (Azure AI Foundry, etc.) and related technologies such as MCP or A2A.
• Experience with data platforms (Databricks, etc.) and organizing, cataloging and chunking of unstructured data for scalable Generative-AI solutions and robust knowledge management.
• Experience with vector stores and graph databases for managing complex relationships to use in AI applications such as recommendation systems.
• Robust experience in Azure AI/Data solutions and a deep understanding of the evolving AI landscape, with proven track record in API integrations for accessing LLMs.
• Demonstrated experience conducting threat modeling and implementing security controls for AI systems, including prompt-injection defenses, data-loss prevention, agent authorization, secure tool execution, secrets management, and adversarial testing.
• Experience operationalizing Responsible AI and model-risk requirements through technical controls, evaluation criteria, documentation, human-in-the-loop patterns, traceability, and auditable evidence.
• Advanced software engineering skills in Python and API/service development, with experience designing distributed, resilient, containerized systems and implementing automated testing
• Experience with Agile/SAFe delivery and CI/CD practices for AI solutions.
• Significant experience working with structured and unstructured data.
• Significant experience in developing sophisticated algorithms to automate processes and tasks.
• Advanced knowledge of current AI technologies and concepts.
  
  

  Equal Opportunity Employer: We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.