GenAI Engineer - Agentic AI & Cloud Engineering

Title : GenAI Engineer - Agentic AI & Cloud Engineering
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 Responsibilities

GenAI & 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 Skills

Generative 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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