Senior Generative AI Engineer

Quevera LLC is supporting an enterprise Generative AI optimization engagement for a large-scale customer in Herndon, VA and Springfield, VA (onsite). In this role, you will help modernize GenAI on AWS, working embedded with customer Scrum teams to design and implement production-ready capabilities such as model routing and orchestration, conversation-context solutions, and integration-ready GenAI services.

What you’ll build

• Design and implement intelligent model-routing logic using ML-based classification to route requests to appropriate LLMs based on conversational context, task complexity, and performance requirements.
• Build and maintain orchestration layers using AWS Bedrock, LangChain, or custom frameworks to support multi-model workflows.
• Train, evaluate, and iterate on classification models using evaluation frameworks and feedback loops.
• Architect conversation-context analysis, retrieval, and embedding strategies to interpret user intent across multi-turn interactions.
• Develop prompt-engineering standards and context-window management techniques that support intent classification and routing.
• Architect enterprise-scale GenAI solutions with high availability, performance optimization, and cost management.
• Apply GenAI platform practices including observability, model evaluation, guardrails, responsible AI controls, and versioning.
• Design and maintain data extraction and transformation pipelines supporting model training, evaluation, and enterprise application integration.

How you’ll work with the customer team

• Engage with customer stakeholders and technical counterparts to gather requirements, validate solutions, and participate in Agile/Scrum ceremonies.
• Collaborate with the Engagement Manager to track progress and risks, producing technical documentation, architecture diagrams, and handoff artifacts.

Requirements

• Active TS/SCI clearance with Polygraph required.
• 5+ years of software development and cloud architecture experience.
• 2+ years of hands-on AWS experience with production workloads.
• 2+ years of experience with Generative AI technologies and LLM deployment.
• Proven track record of enterprise-scale architecture design and implementation.
• Experience with NatSec customers.
• Deep understanding of GenAI foundation models and deployment patterns.
• Strong programming skills in Python and infrastructure-as-code tools.
• Experience with vector databases and semantic search technologies.
• Expert-level knowledge of AWS services, including Amazon Bedrock, OpenSearch Service, CloudWatch, ECS/EKS, and RDS/DynamoDB.
• Strong understanding of security automation and compliance frameworks.
• Ability to work independently and drive initiatives with minimal oversight.
• Strong problem-solving and analytical thinking capabilities, including leading technical discussions and influencing architecture decisions.
• Ability to work in ambiguous, fast-paced environments with a focus on delivering measurable customer outcomes.
• Must be able to obtain and maintain Springfield, VA customer accounts.
• Must be able to travel onsite periodically for meetings and ceremonies.

Technology focus

AWS, Amazon Bedrock, LangChain, Python, OpenSearch Service, CloudWatch, ECS, EKS, RDS, DynamoDB, vector databases, semantic search technologies

Benefits

• 100% employer-paid medical coverage (optional plan)
• Competitive options for Medical, Dental and Vision insurance
• Employer-paid short-term and long-term disability coverage
• Employer-paid life insurance
• $5,000 annually for education, training, certifications, and professional development
• Career advancement through the structured iQTouch Program
• Up to 6% 401(k) match
• Additional 4% profit-sharing contribution (company discretion)

Desired skills

• Ability to contribute to complex technical challenges and prototype innovative solutions.
• Ability to effectively transfer knowledge to customer teams.
• Ability to balance strategic thinking with hands-on implementation.
• Ability to deliver enterprise-grade solutions under tight timelines.