GenAI Engineer – Agentic AI & Cloud Engineering

Title: GenAI Engineer - Agentic AI & Cloud Engineering

The following information aims to provide potential candidates with a better understanding of the requirements for this role. Location : Rockville, MD or McLean, VA Target Start Date : ASAP Type: contract Pay Rate: DOE We are seeking a hands-on GenAI Engineer to help design, build, and productionize enterprise AI solutions focused on agentic systems, LLM-powered workflows, and intelligent automation platforms. This role is centered on building scalable AI tools and frameworks that transform proof-of-concepts into production-ready applications across the organization. The ideal candidate combines strong software engineering fundamentals with deep hands-on experience building AI agents, RAG pipelines, MCP integrations, and cloud-native GenAI applications. This is an engineering-first role for someone who actively codes, architects solutions, and thrives in fast-moving AI environments. This position contributes throughout the software development lifecycle, from architecture and prototyping through deployment, optimization, and operational support. Key ResponsibilitiesGenAI & Agentic System Development

Design and build LLM-powered agent systems using frameworks such as:

LangChain LangGraph AWS Strands Agents SDK or equivalent agent orchestration platforms

Develop and productionize:

AI assistants autonomous and semi-autonomous agents intelligent workflow automation tools MCP-integrated systems RAG-based enterprise search and retrieval solutions

Build agent harness architectures that combine:

LLM reasoning deterministic execution tool orchestration structured output validation guardrails and fallback handling

Implement:

agent memory and context management tool routing and orchestration API integrations vector search and retrieval workflows secure execution tracing and auditing

Partner with teams to take POCs and experimental AI concepts into production-scale initiatives Help drive internal adoption of AI tooling and identify opportunities to expand GenAI capabilities across engineering teams AI Platform Engineering & Cloud Infrastructure

Build scalable AI applications and services on AWS cloud infrastructure Develop backend services and APIs supporting agent workflows and AI tooling Engineer cloud-native AI solutions leveraging:

AWS Bedrock Lambda Step Functions S3 EMR EKS/ECS API Gateway

Contribute to CI/CD pipelines, infrastructure automation, observability, and deployment processes Ensure secure handling of enterprise and sensitive data within AI systems and workflows Data & Retrieval Engineering

Build and optimize retrieval pipelines supporting GenAI applications and RAG architectures Develop SQL and Python-based processing for large-scale datasets and retrieval workflows Work with high-volume cloud data environments and distributed processing systems Support structured and unstructured data ingestion for AI-powered applications Required Technical SkillsGenerative AI & Agentic Systems

Hands-on experience building:

AI agents agentic workflows LLM-powered applications RAG pipelines

Strong understanding of:

prompt engineering memory architectures context management tool usage and orchestration verification and guardrail patterns

Experience integrating with foundation models such as:

Anthropic Claude OpenAI models Amazon Nova or equivalent LLM platforms

Experience communicating with and integrating:

MCP servers APIs external tools enterprise data sources

Programming & Software Engineering

Strong hands-on coding ability in:

Python (primary) SQL

Ability to write:

modular maintainable production-quality code

Experience with:

REST APIs backend engineering automation frameworks test automation CI/CD pipelines

Cloud & Infrastructure

Strong AWS experience including:

Bedrock Lambda S3 EMR Step Functions CloudWatch EKS/ECS

Experience with:

Docker Kubernetes Infrastructure as Code GitLab CI / Jenkins / GitHub Actions

AI Engineering Tooling

Experience using AI-assisted engineering tools such as:

Amazon Q Developer GitHub Copilot Claude ChatGPT

Familiarity with AI-assisted software development workflows and rapid prototyping approaches What Success Looks Like

Deeply hands-on with GenAI engineering Comfortable building systems from concept through production deployment Strong technical depth with the ability to rapidly experiment and iterate Able to bridge AI concepts, engineering implementation, and scalable enterprise adoption Thrives in highly collaborative, innovation-focused environments Nice to Have

Vector databases:

Pinecone FAISS OpenSearch

Model tuning / fine-tuning:

LoRA PEFT managed tuning platforms

Observability tooling:

Grafana Prometheus ELK stack

Experience working in regulated or enterprise-scale environments Education & Experience

Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or related field Experience building enterprise-grade software solutions and cloud-native applications Strong communication and collaboration skills Ability to work in fast-paced, rapidly evolving technical environments

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