Generative AI Engineer

Zillion Technologies, Inc.; McLean (VA); On-site; USD 124,000 - 131,000; Full time

Job summary

Zillion Technologies, Inc. in McLean, VA seeks an Applied AI Engineer for on-site collaboration five days a week.

You will design, develop, and deploy enterprise-grade GenAI solutions, focusing on trace evaluation, spec-based development, language-model evaluation, and knowledge base integration. You will lead architecture for AI agents, evaluate LLMs, and build multimodal, scalable pipelines with Spark, Kubernetes, and cloud-native tools while enforcing rigorous testing, guardrails, and

Qualifications

• Production-grade AI feature development with clear specs.
• Experience with agentic workflows and evaluation guardrails.
• Experience with GenAI design and testing.

Responsibilities

• Architect scalable AI agents and agentic workflows.
• Develop and evaluate LLMs (Claude, Azure OpenAI, open-source).
• Fine-tune open weight models where needed.
• Design and deploy vector databases and knowledge bases.
• Curate enterprise data connectors for AWS Bedrock/Elastic.
• Implement MCP and A2A communication.
• Maintain notebooks on SageMaker, MLFlow, Kubeflow.
• Integrate GenAI with enterprise platforms via APIs.
• Establish evaluation with DeepEval and bias/safety guardrails.
• Design ingestion pipelines for diverse media sources.
• Orchestrate multimodal ETL/ELT with Spark.
• Map media to vector representations with vector stores.

Skills

Python

Spark

Git

LLMs

Prompt engineering

CI/CD

AWS SageMaker

Vector databases

Multimodal models

Education

Bachelor’s degree in CS/DS/AI/ML

Master’s degree preferred

Tools

AWS Bedrock

Kubeflow

MLflow

Elastic

MongoDB Atlas

Docker

Kubernetes

Job description

Work sponsorship is not available for this position.

Job Title: Applied AI Engineer

Locations: Onsite in Mclean, VA (5 days a week)

Interview Type: In-Person

Must Have Qualifications

Must have proven experience as an Applied AI Engineer with deep expertise in modern AI workflows, GenAI application design, and spec-based development. Must demonstrate rigorous software engineering discipline in designing and shipping production AI features by authoring clear functional specifications, orchestrating agentic workflows, and maintaining strict evaluation and testing guardrails.

Overview

We are seeking a highly skilled Applied AI Engineer with deep expertise in modern AI frameworks and workflows. You will design, develop, and deploy advanced AI models and intelligent systems, focusing on Trace Evaluation, Spec-Based Development, Language Model Evaluation, Graph DB, and AWS Knowledge Base integration. As a hands-on technical leader, you will collaborate with cross-functional teams to deliver enterprise grade Gen AI solutions.

Key Responsibilities

• Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications for complex business use cases.
• Develop and evaluate LLMs (e.g., Claude, Azure OpenAI, open-source models).
• Seek candidates with experience fine-tuning open weight models.
• Design and deploy systems using vector databases and knowledge bases.
• Curate enterprise data with connectors integrated into AWS Bedrock Knowledge Base/Elastic.
• Implement Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication.
• Build and maintain Jupyter notebooks on platforms like SageMaker, MLFlow, and Kubeflow (on Kubernetes/EKS).
• Integrate GenAI solutions with enterprise platforms via APIs and standardized GenAI patterns.
• Establish validation procedures using Evaluation Frameworks (DeepEval), bias mitigation, safety protocols, and guardrails.
• Design robust ingestion pipelines for extracting, chunking, enriching, and anonymizing data from various media sources.
• Orchestrate multimodal pipelines with scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows.
• Implement embedding-driven workflows, mapping media content to vector representations and integrating with vector stores (AWS KnowledgeBase/Elastic/Mongo Atlas).

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, AI/ML, or related technical field (Master’s preferred).
• Advanced proficiency in Python, big data technologies (e.g., Spark, Hadoop), and data manipulation libraries (e.g., Pandas, NumPy).
• Solid knowledge of classical ML algorithms, deep learning architectures, LLMs, generative AI, and reinforcement learning.
• Hands-on experience with Microsoft Azure, Azure OpenAI, and AWS cloud platforms.
• Strong understanding of Spec-Based Development, Git, and CI/CD best practices.
• Expertise in prompt engineering, vector databases (AWS KnowledgeBase/Elastic), and multimodal models.
• Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow on EKS).
• Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.).
• Deep understanding of GenAI architectural patterns and Evaluation Frameworks (DeepEval).
• Demonstrated ability to work in cross-functional agile teams.
• Github Code Repository Link required for each candidate.
• Thorough vetting is mandatory.

Preferred Qualifications

• Experience in financial, regulatory technology, or enterprise automation.
• Familiarity with MLOps tools (MLflow, Kubeflow, Weights & Biases).
• Contributions to open-source AI projects or research publications.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Experience with Spark is optional but preferred.

Benefits

We offer a benefits package including medical, dental, vision, and 401(k).

Compensation

$90.00 - $95.00 per hour. This is the targeted compensation range for this role per year. Please note that this range is provided as a guideline and the final offer will be based on several factors, including but not limited to, skillset and competencies, level of experience, education, certifications, and location.

We are an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other characteristic protected by applicable federal, state, or local law.