GenAI Engineer
Greenbelt, MD, 20770
Reference ID: 31880300
Date Posted: 03/14/2026
Job Title: GenAI Engineer
Location: Hybrid – Tysons, VA (8350 Broad St, Tysons, VA 22102)
Schedule: 3 days onsite (Monday, Tuesday, Thursday) | 9:00 AM – 5:00 PM ET
Employment Type: Permanent
Salary Range: $130,000 – $135,000
Role Overview
We are seeking a hands-on GenAI Engineer to design, develop, and deploy scalable AI/LLM-powered solutions in a pure AWS environment. This role sits at the intersection of AI engineering and data engineering and will focus on ingesting and transforming enterprise data to power machine learning models, LLM workflows, and AI-driven business initiatives.
This is not a single-project role. You will serve as a foundational AI/data engineering contributor supporting enterprise AI adoption across teams.
Key Responsibilities
AI & Generative AI Engineering
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Design, build, and deploy production-grade LLM-powered applications and AI systems
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Develop Retrieval-Augmented Generation (RAG) pipelines integrating Snowflake data
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Implement prompt engineering strategies (prompt chaining, few-shot learning, CoT, ToT, structured outputs)
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Select and evaluate foundation models (OpenAI, Hugging Face, AWS Bedrock, etc.)
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Build or support AI models including:
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Lead scoring
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Classification
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Regression
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LLM-related use cases
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Implement AI guardrails, hallucination mitigation, and responsible AI practices
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Support LLMOps / MLOps workflows including deployment, monitoring, and versioning
Data Engineering & Snowflake Integration
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Engineer and ingest vendor and internal datasets
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Build ETL/ELT pipelines to transform and prepare data for AI models
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Optimize Snowflake queries and cost efficiency
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Implement vector search and embeddings pipelines
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Ensure enterprise data governance and security standards
AWS & Cloud Engineering
Architect scalable AI solutions leveraging:
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AWS Bedrock & SageMaker (model access and fine-tuning)
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Lambda (serverless AI deployment)
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EC2 (GPU-based inference workloads)
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Step Functions (AI workflow orchestration)
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CloudWatch (monitoring & observability)
Must-Have Qualifications
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5 years of experience in AI/ML, Software Engineering, or Data Engineering
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Recent hands-on AI/ML experience
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Strong Python programming skills
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Experience building data pipelines feeding ML/AI models
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Experience with AWS cloud services
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Experience working with Snowflake or modern enterprise data platforms
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Understanding of ML lifecycle (training, evaluation, deployment)
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Ability to clearly explain AI workflows and methodologies
Preferred Qualifications
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Experience building RAG pipelines in enterprise environments
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Experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.)
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Experience with agentic AI frameworks (AutoGen, CrewAI, etc.)
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Experience with vector databases and embeddings
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Knowledge of MLOps best practices
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Background in media, marketing analytics, or enterprise sales platforms
Current Initiative
Initial focus will be on:
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Building AI-driven lead scoring models
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Generating targeted sales leads using enterprise and vendor data
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Engineering Snowflake data pipelines to support AI modeling
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Partnering with sales teams to validate and refine model outputs
Team Environment
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Pure AWS cloud environment
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Cross-functional collaboration (Data Engineers, DevOps, Architects, QA, Python Developers)
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Offshore team collaboration experience preferred
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Fast-paced, fail-fast AI experimentation culture
Soft Skills
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Strong communication skills
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Professional and collaborative
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Creative problem solver
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Ability to translate business problems into AI-driven solutions
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Comfortable explaining technical AI concepts to non-technical stakeholders
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