Applied AI Engineer

Position: Applied AI Engineer
Location: McLean, Virginia
Duration: Contract
Job ID: 181252
Job Overview:
An Applied AI Engineer is needed to design, build, and deploy advanced, production-grade GenAI and AI/ML solutions in a highly collaborative, on-site environment. This role focuses on modern AI workflows, including spec-based development, agentic workflows, language model evaluation, and integration with cloud-native data and knowledge platforms. The engineer will serve as a hands-on technical leader, working closely with cross-functional teams to deliver scalable, secure, and well-governed AI capabilities that support complex enterprise use cases.
Responsibilities:

• Design, architect, and implement scalable AI agents, agentic workflows, and GenAI applications for complex business and enterprise use cases.
• Develop, fine-tune, and evaluate large language models (LLMs), including Claude, Azure OpenAI models, and open-source/open-weight models.
• Design and deploy systems leveraging vector databases and knowledge bases to support retrieval-augmented generation and intelligent search.
• Curate and integrate enterprise data into AWS Bedrock Knowledge Base and Elastic using appropriate connectors and ingestion strategies.
• Implement Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication patterns to enable robust multi-agent systems.
• Build, maintain, and optimize Jupyter notebooks on platforms such as SageMaker, MLflow, and Kubeflow running on Kubernetes/EKS.
• Integrate GenAI solutions with enterprise platforms and services via APIs and standardized GenAI architectural patterns.
• Establish and maintain rigorous validation procedures using evaluation frameworks (such as DeepEval), including bias mitigation, safety protocols, and guardrails.
• Design and manage robust ingestion pipelines for extracting, chunking, enriching, and anonymizing data from diverse media sources.
• Orchestrate multimodal data pipelines using scalable frameworks (e.g., Apache Spark, PySpark) to support automated ETL/ELT workflows.
• Implement embedding-driven workflows that map media content to vector representations and integrate with vector stores (e.g., AWS Knowledge Base, Elastic, Mongo Atlas).
• Collaborate with cross-functional agile teams, including product, data, and engineering stakeholders, to translate specifications into production-ready AI features.
• Author clear, detailed functional specifications and technical documentation for AI features and workflows.
• Apply rigorous software engineering discipline, including code reviews, testing, and CI/CD practices, to ensure reliable and maintainable AI systems.
• Continuously monitor, evaluate, and improve AI models and pipelines in production, addressing performance, drift, and quality issues.
• Contribute to the definition and adoption of best practices for GenAI architecture, evaluation, and governance across the organization.

Qualifications:

• Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical field; Master's degree preferred.
• Proven experience as an Applied AI Engineer with deep expertise in modern AI workflows, GenAI application design, and spec-based development.
• Demonstrated ability to design and ship production AI features using clear functional specifications, agentic workflows, and strict evaluation/testing guardrails.
• Advanced proficiency in Python, including experience with data manipulation libraries such as Pandas and NumPy.
• Hands-on experience with big data technologies such as Spark and Hadoop, and familiarity with scalable data processing patterns.
• Solid knowledge of classical machine learning algorithms, deep learning architectures, LLMs, generative AI, and reinforcement learning concepts.
• Strong experience with Microsoft Azure, Azure OpenAI, and AWS cloud platforms for AI/ML and GenAI workloads.
• Expertise in spec-based development practices, Git, and CI/CD best practices for deploying AI services and pipelines.
• Proficiency in prompt engineering and working with vector databases and knowledge bases (e.g., AWS Knowledge Base, Elastic).
• Hands-on experience with cloud-native AI development tools such as AWS SageMaker, Bedrock, and MLflow on EKS or similar platforms.
• Strong programming skills with ML and GenAI libraries and frameworks (e.g., Transformers, LangChain, and related ecosystems).
• Deep understanding of GenAI architectural patterns and evaluation frameworks such as DeepEval.
• Demonstrated success working in cross-functional agile teams, collaborating with product managers, data scientists, and engineers.
• Ability to design and implement robust data ingestion, transformation, and anonymization pipelines for multimodal data.
• Experience integrating AI solutions with enterprise systems via APIs and standardized integration patterns.
• Preferred experience in financial services, regulatory technology, or large-scale enterprise automation environments.
• Familiarity with MLOps tools such as MLflow, Kubeflow, and Weights & Biases for experiment tracking and model lifecycle management.
• Experience with containerization and orchestration technologies, including Docker and Kubernetes.
• Experience with Spark (including PySpark) is optional but strongly preferred for large-scale data processing.
• Contributions to open-source AI projects, research publications, or public code repositories are a plus.
• Ability to work full-time on-site and thrive in a collaborative, cross-functional agile environment.
• Eligibility to work in the United States without sponsorship, as a direct W-2 employee to the vendor.
• Github code repository link required to demonstrate prior AI/ML and GenAI engineering work.

About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit ;br>
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Pay Range: $80- $85/hr
The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work.
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