AI Engineer

Lightedge•Ashburn, VA

About The Position

Position Summary The AI Engineer plays a central role in designing, developing, and integrating AI-driven capabilities across Lightedge’s core data and operational systems. This position bridges strategy and execution—translating business problems into scalable AI solutions that enhance automation, analytics, and decision-making. The ideal candidate combines technical expertise in AI/ML, systems integration, and data architecture with strong business acumen to deliver measurable impact through intelligent automation and data-driven insight. Key Responsibilities AI Software Development: Design, develop, and maintain production-grade AI/ML code, services, and integrations. Build and iterate on AI prototypes, proofs of concept, and production systems. Contribute to codebases, CI/CD pipelines, and engineering standards for AI solutions. Collaborate with teams to ensure maintainable, testable, and scalable implementations. Design and operate agent-driven systems that autonomously execute workflows, with humans providing oversight, governance, and continuous optimization. AI Use Case Development: Partner with business units to identify and evaluate high-value AI opportunities that align with Lightedge’s strategic goals. Solution Architecture: Contribute to the design of scalable and cyber-resilient AI and ML solutions, ensuring seamless integration with enterprise systems (e.g., ServiceNow, CRM, ERP, data lake). System Integration: Collaborate with data engineering and platform teams to operationalize AI models and embed intelligence into workflows and customer experiences. Data Strategy Alignment: Ensure all AI initiatives align with enterprise data governance, security, and privacy standards. Innovation Evangelism: Act as a technical and strategic advisor to business stakeholders on how to responsibly leverage emerging AI technologies. Cross-Functional Collaboration: Work closely with product management, IT, and Operations, and Security teams to ensure a secure, resilient, consistent delivery, and maintainability. Communications: Regularly communicate with executive leadership and business stakeholders to align AI strategy with organizational goals. Optimize: Monitor, evaluate, and optimize the performance of deployed AI models and systems. Maintain: Own post-deployment support, monitoring, and continuous improvement of AI systems until transitioned to long-term support. Cyber Resilience: Ensure that all underlying systems are protected against cybersecurity threats and can recover rapidly in the event of a cyberattack or unexpected system outage. Documentation and Governance: Develop and implement AI governance frameworks and ensure ethical AI practices, including m aintenance of architectural diagrams, model documentation, and compliance records for AI systems Assist Sales: Work with the Sales team as needed, serving as an AI SME during the sales cycle for new customers.

Requirements

Proficiency in Python for AI/ML and data processing
Experience with one or more of JavaScript/TypeScript, Java, or C# for API and application development.
Experience with building microservices, distributed systems, CI/CD Pipeline, and DevOps practices.
Experience evaluating AI model outputs, including prompt testing, benchmarking, and performance tuning
Knowledge of vector databases, RAG pipelines, or LLM orchestration frameworks.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or equivalent experience.
3+ years of experience working with machine learning, NLP, or generative AI technologies, including RAG pipelines, vector databases, and prompt engineering
Strong proficiency in cloud platforms (Azure, AWS, or GCP) and API-based integrations.
Experience deploying models via REST APIs, data pipelines, or event-driven frameworks.
Working knowledge of data governance, model monitoring, and security principles.
Excellent communication skills and ability to translate technical concepts into business value.

Nice To Haves

Experience integrating AI models into ServiceNow, Salesforce, or similar enterprise platforms.
Experience building LLM-based applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel
Experience developing AI-powered applications such as chatbots, copilots, or intelligent automation tools
Experience with prompt engineering, evaluation, and tuning of generative AI systems
Experience with SQL and working with large-scale data systems
Familiarity with embedding models and vector search optimization
Familiarity with MLOps tools (MLflow, Vertex AI, SageMaker, Databricks, etc.).
Previous experience leading cross-functional AI or automation initiatives.
Certifications in cloud architecture or AI engineering (e.g., Azure AI Engineer, AWS Machine Learning Specialty).
Experience with AI inferencing engines such as vLLM or SGLANG
Kubernetes Experience.
Experience with Enterprise LLMs including ChatGPT, Claude, Gemini, and Copilot.

Responsibilities

Design, develop, and maintain production-grade AI/ML code, services, and integrations.
Build and iterate on AI prototypes, proofs of concept, and production systems.
Contribute to codebases, CI/CD pipelines, and engineering standards for AI solutions.
Collaborate with teams to ensure maintainable, testable, and scalable implementations.
Design and operate agent-driven systems that autonomously execute workflows, with humans providing oversight, governance, and continuous optimization.
Partner with business units to identify and evaluate high-value AI opportunities that align with Lightedge’s strategic goals.
Contribute to the design of scalable and cyber-resilient AI and ML solutions, ensuring seamless integration with enterprise systems (e.g., ServiceNow, CRM, ERP, data lake).
Collaborate with data engineering and platform teams to operationalize AI models and embed intelligence into workflows and customer experiences.
Ensure all AI initiatives align with enterprise data governance, security, and privacy standards.
Act as a technical and strategic advisor to business stakeholders on how to responsibly leverage emerging AI technologies.
Work closely with product management, IT, and Operations, and Security teams to ensure a secure, resilient, consistent delivery, and maintainability.
Regularly communicate with executive leadership and business stakeholders to align AI strategy with organizational goals.
Monitor, evaluate, and optimize the performance of deployed AI models and systems.
Own post-deployment support, monitoring, and continuous improvement of AI systems until transitioned to long-term support.
Ensure that all underlying systems are protected against cybersecurity threats and can recover rapidly in the event of a cyberattack or unexpected system outage.
Develop and implement AI governance frameworks and ensure ethical AI practices, including m aintenance of architectural diagrams, model documentation, and compliance records for AI systems
Work with the Sales team as needed, serving as an AI SME during the sales cycle for new customers.