AI Engineer at lightedge

<div> <p style="line-height: normal; margin: 0in 0in 8pt; font-size: 12pt; font-family: Aptos, sans-serif;">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.</p> <p style="line-height: normal; margin: 0in 0in 8pt; font-size: 12pt; font-family: Aptos, sans-serif;">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.</p> </div> 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 maintenance 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. Required Qualificiations • 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. Preferred Qualifications • 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. Success Metrics • Increased AI-enabled automation efficiency and accuracy across business processes. • Reduction in manual data handling through intelligent integrations. • Timely delivery of production-ready AI capabilities. • Cross-departmental adoption of AI solutions. • Measurable business ROI from deployed AI initiatives.