AI/ML Engineer

Xperteez Technology; Washington (District of Columbia); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Xperteez Technology is seeking an AI/ML Engineer in Washington, DC to advance mission-critical government initiatives and proprietary AI infrastructure. You will work with large language models, retrieval-augmented generation, and multi-agent orchestration to build secure, scalable ML systems.

The role involves cross-functional collaboration, knowledge of frontier AI platforms, and hands-on experience with cloud AI services across GovCloud/Azure Vertex AI.

Qualifications

• Proficiency in Python for AI/ML development.
• Hands-on experience with LLMs, RAG systems, and prompt engineering.

Responsibilities

• Design, implement, and optimize AI/ML models leveraging LLMs, RAG, and prompt engineering for production-grade apps.
• Develop and orchestrate multi-agent systems using LangGraph and LangChain.
• Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust data pipelines, manage ETL processes, and develop metadata catalogs for high-quality data.
• Create and maintain REST APIs and SDK integrations to facilitate data and model interactions.
• Collaborate with product, security, and engineering teams to ensure secure coding and CI/CD practices.
• Document technical decisions and communicate complex concepts clearly to stakeholders.

Skills

Python

LLMs

RAG

AWS

LangGraph

LangChain

AWS GovCloud

Tools

LangGraph

LangChain

AWS GovCloud

Job description

Job Title: AI/ML Engineer

Job Type: Full-Time

Location: Washington, DC - (Onsite / Hybrid)

Required Skills

• Python
• LLMs
• RAG
• AWS

Job Summary

Join our team as a AI/ML Engineer and play a pivotal role in driving mission-critical government initiatives while also contributing to proprietary AI infrastructure, you’ll harness advanced large language models (LLMs), retrieval-augmented generation (RAG), and multi-agent orchestration to deliver secure, scalable, and impactful machine learning systems. You’ll work closely with cross-functional experts, leveraging frontier AI platforms and the latest in agentic AI tooling.

Key Responsibilities

• Design, implement, and optimize AI/ML models particularly leveraging LLMs, RAG, and prompt engineering for production grade applications.
• Develop and orchestrate multi-agent systems using frameworks such as LangGraph and LangChain.
• Integrate and deploy solutions on secure cloud environments, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, and AWS Bedrock.
• Build robust data pipelines, manage ETL processes, and develop metadata catalogs and ontologies to ensure high-quality data for AI training and inference.
• Create and maintain REST APIs and SDK integrations to facilitate seamless data and model interactions.
• Collaborate with product, security, and engineering teams to ensure best-in-class delivery, following secure coding and DevOps best practices (CI/CD).
• Document technical decisions and communicate complex concepts clearly to both technical and non-technical stakeholders.

Required Skills and Qualifications

• Proficiency in Python for AI/ML development, including experience with REST APIs and SDK integration.
• Hands‑on experience with LLMs, RAG systems, and prompt engineering in production environments.
• Familiarity with multi‑agent orchestration, tool use, and frameworks like LangGraph and LangChain.
• Deep understanding of cloud AI services (AWS GovCloud, Google GovCloud, Azure IL5+, Vertex AI, AWS Bedrock).
• Background in building and maintaining data pipelines, ontologies, metadata catalogs, and ETL processes.
• Strong grasp of secure coding and modern DevOps practices (CI/CD pipelines).
• Exceptional written and verbal communication skills for effective collaboration and documentation.

Preferred Qualifications

• Experience with AI/agentic platforms, such as Anthropic for Gov, OpenAI Enterprise, Gemini Enterprise, or Grok Enterprise.
• Knowledge of metadata catalog platforms (MCP) and advanced API development techniques.
• Prior exposure to government or highly regulated cloud environments and compliance standards.