Contract Knowledge Graph Software Engineer Jobs in Washington

AI/ML Software Engineer

Company: ZIO Technologies, Inc.
Location: Remote (U.S.-based) with occasional onsite requirements
Duration: Long-term engagement (up to 5 years)

About the Opportunity

ZIO Technologies is seeking a highly skilled AI/ML Software Engineer to support a long-term AI/ML initiative focused on building intelligent systems that automate tasks, enhance internal workflows, and improve user-facing services.

Scope of Work

The AI/ML Software Engineer will:

• Build software tools that incorporate AI/ML techniques to automate narrowly defined tasks with high accuracy

• Assist internal users with their job functions

• Improve the experience external users have when interacting with systems

This includes, but is not limited to:

• RPA work

• Building or refining chatbots

• Incorporating AI/ML into reporting tools

• Building LLM agents for knowledge retrieval, deep research, translation, transcription, redaction, document analysis, document generation, agentic coding, and data processing

Key Responsibilities

System Design & Collaboration

• Work within established constraints regarding infrastructure, programming languages, and model selection

• Contribute to technical decision-making related to data processing, retrieval strategies, and system integration

• Collaborate with team members to define agent architectures, workflows, and system design decisions

• Evaluate and select appropriate approaches for given tasks, including determining when to use LLM-based versus non-LLM techniques

• Design and build software systems that integrate AI/ML techniques

Testing, Evaluation, and Quality Assurance

• Assist in the design and implementation of testing and evaluation pipelines for AI/ML systems

• Develop unit and integration tests for AI-enabled workflows and data pipelines

• Generate and utilize synthetic data to support evaluation and benchmarking efforts

• Contribute to improving system performance, including accuracy, latency, and cost efficiency

Deployment & Operations

• Support deployment of AI/ML applications within a hybrid cloud environment

• Work with containerized applications to ensure reliable deployment and updates

• Optimize systems for environments with limited computational resources, including minimal GPU availability

General Responsibilities

• Deliver production-grade systems aligned with defined requirements

• Document system designs, workflows, and technical decisions

• Stay informed on relevant advancements in AI/ML and apply them where appropriate

What You'll Work On (Multi-Year Deliverables)

This role supports a multi-year AI/ML roadmap. Key initiatives include:

Year 1

• Internal chatbot refinement (UI improvements, user history, feedback)

• External chatbot development (conversational, user-facing)

• RPA tools using local LLMs and batching

• Knowledge retrieval improvements (RAG, vector search, system integration)

• AI capabilities for translation, transcription, and redaction

Year 2

• Chatbot personalization and workflow integration

• RPA automation with reporting and analytics

• Expanded knowledge retrieval with permission-based indexing

• Deep research capabilities using graph-based retrieval (graphRAG)

• Document analysis using NLP and graph techniques

Year 3

• Scaling chatbot systems for broader deployments

• Case management integration and data centralization

• Advanced automation for case review and updates

• Structured data extraction from documents

• Initial document generation (PDFs, forms)

Year 4

• Low-code AI agent builder for internal use

• Workflow-integrated chatbot systems

• AI-enhanced reporting and automation expansion

• Fine-tuning embeddings and small language models

• Expanded document and content generation capabilities

Year 5

• Public-facing AI retrieval capabilities

• Integration of transcription into operational systems

• Advanced document modification using AI and automation

• End-to-end workflow integration of retrieval, research, and automation

Minimum Qualifications (Required)

• Bachelor of Science in Engineering, Computer Science, Data Science, or Mathematics, or a related field

Preferred Qualifications

• At least three (3) years' experience in data science, machine learning, or applied AI development

• At least three (3) years' experience in software engineering, architecture, or web development

Required Skills, Experience, & Capabilities

Technical Experience

• SQL and relational database systems (e.g., PostgreSQL)

• Fine-tuning small language models or embedding models

• Graph databases or graph extensions (e.g., Neo4j, Apache AGE)

• Designing and implementing multi-agent or task-oriented AI systems

• Embedding models, vector similarity, re-ranking, and graph retrieval techniques in RAG systems

• Version control systems (e.g., Git), containerization technologies (e.g., Docker), and service-oriented architectures

• Collaborating with large language models (LLMs), including both API-based integration and local deployment

• Validating AI-generated outputs, mitigating hallucinations, and integrating AI tools into production pipelines

Core Engineering Capabilities

• Strong proficiency in Python, including backend services, APIs, middleware, and data pipelines

• Understanding of data structures, algorithms, and clean coding principles

• Ability to select and apply appropriate techniques (LLM and non-LLM)

• Ability to design and implement AI/ML systems operating on complex, inconsistent, or evolving datasets while balancing accuracy, latency, and cost

Additional Knowledge Areas

• Hybrid cloud environments and distributed system considerations

• Threading, asynchronous processing, and queues in backend systems

• React and chatbot UI development

• Classical natural language processing (NLP) techniques in addition to LLM-based approaches

• Data science and LLM-related libraries in performance-oriented programming languages

Work Environment & Requirements

• Work is primarily remote within the United States

• Must be available Monday through Friday, 8:00 AM to 4:30 PM EST

• Flexibility to support evenings, weekends, or extended hours as needed

• Must be able to report onsite within seventy-two (72) hours if required

• Initial onboarding may require onsite presence

Security & Compliance Requirements

• Must use approved technologies for all work

• No use of personal devices to access systems

• No external file sharing outside approved environments

Additional Information

• This role supports a long-term, large-scale AI/ML initiative

• Candidates must be authorized to work in the United States