Why This Role Stands Out
This role offers an exciting opportunity to shape the future of enterprise AI by building cutting-edge GenAI solutions and driving them from concept to production. You'll thrive here if you're a skilled engineer passionate about agentic AI, RAG pipelines, and hands-on cloud engineering, eager to contribute to innovative projects. Apply now to be at the forefront of AI development and make a significant impact.
Quick Overview
Job Description
Title: GenAI Engineer – Agentic AI & Cloud Engineering
Location: Rockville, MD or McLean, VA (Hybrid)
Contract: 6+ months contract with extension
Only Local candidates who can take Assessment and only who are in DC/VA/MD who can got for F2F intervie
Job Description
This role sits within a GenAI-focused engineering team responsible for taking early-stage AI concepts and driving them from POC to production. The team is heavily focused on building AI-powered tools, agents, and enterprise use cases leveraging modern GenAI frameworks.
Key Responsibilities
- Design and build GenAI solutions, including:
- Agent-based architectures
- RAG (Retrieval-Augmented Generation) pipelines
- AI-powered tools and automation workflows
- Develop and maintain agent frameworks, including integration with MCPs (Model Context Protocols / multi-component systems)
- Take proofs of concept (POCs) and:
- Mature them into scalable solutions
- Drive adoption across teams
- Bring them into production environments
- Partner across teams to “market” and evangelize AI solutions internally
- Work hands-on across the stack, including coding, architecture, and infrastructure design
- Operate in a high data volume environment, requiring strong data engineering fundamentals
Required Technical Skillset
- GenAI / LLM Engineering (core requirement):
- Experience building agents and AI workflows
- Hands-on with RAG pipelines
- Strong understanding of LLM integration and orchestration
- Programming & Data:
- Python (primary language for AI/agent development)
- SQL (data access, transformation, querying large datasets)
- Experience working with large-scale data environments
- Cloud & Infrastructure:
- Strong experience with AWS
- Understanding of deploying and scaling AI solutions in cloud environments
- Engineering Mindset:
- Hands-on coder (not purely conceptual/architectural)
- Ability to build from scratch and iterate quickly
What “Good” Looks Like
- Deep, hands-on GenAI builder (not just theoretical AI knowledge)
- Proven ability to:
- Build working agents and AI tools
- Take ideas from concept → POC → production
- Comfortable operating in ambiguous, fast-moving environments
- Strong communicator who can drive adoption across business and tech teams
Team & Environment
- Focused on AI-first innovation and experimentation
- Working on a pipeline of multiple POCs and emerging initiatives
- Highly collaborative, cross-functional engagement
- Based in FINRA office environment (onsite expectations likely)
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