This version positions the role as a hybrid AI Engineer + Business Intelligence Developer, to build AI solutions while also delivering executive reporting, KPI dashboards, and measurable business outcomes. 3+ years of experience building production-level AI or ML systems, including LLMs, AI agents, or complex automation frameworks.[KN1.1].
Numbers & Facts
Location
Reston, VA
Salary
$88.18–$93.18 Per Hour
Description
Our Client, a Health Insurance company, is looking for a Agentic AI Engineer / AI Developer (with Business Intelligence & Reporting) for their Reston, VA/Hybrid location.
Responsibilities:
25% Lead a team of software engineers in the design, development, and implementation of multiple applications. Performs and leads the detail technical design, coding, code review and testing of new applications and enhancements of existing applications. Serves as a subject matter expert for specified systems and their subsequent applications. Develop and/or analyze interface design documentation. Comply with hardware and software systems standards and procedures.
Deliver large systems for tens of thousands of users. Ensures compliance to the dev/sec/ops practices and policies. Understanding of architectural practices and design.
25% Identifies gaps in requirements and solves problems for the supporting staff. Identifies sequencing of services and technologies that are integrated in later phases of the project. Leads the evaluation of risk and opportunity impacts to existing or proposed projects/programs and implements risk mitigation actions. Develops ways to improve performance and increase system availability. Provides recommendations to infuse new technology. Compile, assess, and report data results from software testing and analysis.
25% Supports the Project Manager as the technical team lead on the project. Estimates the technical costs of projects for clients and project managers. Confers with clients to identify requirements and determine desired outcomes to formulate the design of the system or offer alternatives. Demonstrated experience with front-end and back-end programing and integration frameworks and tools. Assist in the estimation of development of application features.
25% Leads software design and development teams. Identifies, analyzes, defines, and coordinates user, customer, and stakeholder needs and translates them into technical requirements. Manages technical resources (hardware, software, licenses, and services). Plans and leads transformation initiatives to new software architectures. Extend open-source libraries and systems as necessary to meet the needs of the team. Play a crucial role in product scoping and roadmap / architecture discussions. Continually evaluate emerging technologies to identify opportunities, trends, and best practices. Ensure code quality, deployment standards and practices. Mentoring junior developers.
Requirements:
Bachelor's Degree
Education details:
Information Technology or Computer Science
Experience:
8 years Software design and development, software test and evaluation, software requirements management
In lieu of education
In lieu of a Bachelor's degree, an additional 4 years of relevant work experience is required in addition to the required work experience.
Ai & software engineering
3+ years of experience building production-level AI or ML systems, including LLMs, AI agents, or complex automation frameworks.[KN1.1]
3+ years of experience with Python and Python libraries such as Pandas, NumPy, and related data processing tools.
Experience with Large Language Models (LLMs), Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL).[KN2.1]
Strong understanding and hands-on experience with Natural Language Processing (NLP).
Experience with AI agent frameworks and tools such as LangGraph, LangChain, TensorFlow, or PyTorch.
Experience optimizing workflows through intelligent automation and AI-driven solutions.
Experience integrating AI agents with APIs, cloud platforms, enterprise applications, and databases.[KN3.1]
Experience building and deploying AI pipelines on AWS SageMaker with Aurora PostgreSQL for data ingestion, analytics, and operational reporting.
Experience performing automated testing, troubleshooting, and application maintenance.
Experience with Software Development Lifecycle (SDLC) methodologies, including DevSecOps practices.
Experience with cloud platform - Amazon Web Services (AWS).[KN4.1]
Experience developing RESTful services using Java and Spring Boot.
Experience managing CI/CD pipelines and containerized deployments using Kubernetes, Docker, Jenkins, or similar technologies.
Preferred experience using GitHub and collaborative development platforms.
Business Intelligence & Analytics
3+ years of experience designing and developing business intelligence solutions and enterprise reporting platforms.
Experience creating interactive dashboards and reports using tools such as Power BI, Tableau, or similar BI platforms.[KN5.1]
Hands-on expertise with SQL, data querying, and relational database concepts.
Experience developing data models, semantic layers, KPIs, scorecards, and performance metrics for business stakeholders.
Experience integrating and transforming data from multiple enterprise systems and APIs for reporting and analytics purposes.
Knowledge of data warehousing, ETL/ELT processes, data governance, and data quality management.
Ability to analyze business requirements and translate them into meaningful visualizations and actionable insights.
Experience building operational, executive, and analytical reports that support strategic decision-making.
Understanding of data visualization best practices, reporting standards, and storytelling with data.
Experience measuring and reporting AI solution performance, adoption metrics, operational efficiencies, and business outcomes.
Strong communication skills with the ability to present technical and analytical findings to both business and executive audiences.
Preferred Qualifications
Experience combining AI/ML capabilities with BI platforms to deliver intelligent reporting and decision-support solutions.
Experience with Azure Data Factory, Databricks, Snowflake, Redshift, Synapse, or similar modern data platforms.
Familiarity with MLOps, DataOps, and analytics engineering practices.
This version positions the role as a hybrid AI Engineer + Business Intelligence Developer, to build AI solutions while also delivering executive reporting, KPI dashboards, and measurable business outcomes.