SR. AI ENGINEER

Location Requirements: This position can sit remotely (anywhere in the US) or hybrid to Wayne, PA or Naperville, IL. The role will work hours based on the Eastern Time Zone.
This position reports to the Sr. Director of CX-AI Engineering and partners with Customer Experience, Development, Architecture, Product, and Strategic partners to design and deliver services that strengthen customer satisfaction and optimize product performance.
Your role on the team:
We’re looking for a hands-on AI Engineer to design, build, and ship customer-facing, production-grade features powered by modern LLMs. You’ll partner with product, data, platform, and Customer Experience/Support to turn messy real-world problems into reliable, safe, and measurable AI solutions. You’ll close the loop from voice-of-customer insight model/design choices launch telemetry and iteration, with success measured by outcomes like task completion, CSAT, time-to-resolution, and deflection rate—not just model scores.
You will help develop the next-generation agentic platform that powers customer-facing assistants across the entire journey—from discovery and onboarding to in-product guidance and support. These agents will reason, plan, call internal tools/APIs, retrieve knowledge, and escalate to humans gracefully. You’ll collaborate with CX/Support, Product, and Platform to integrate with CRM and knowledge bases, implement memory and personalization, enforce safety/quality guardrails, and run evaluations and A/B tests. Success is measured in real CX outcomes: shorter time-to-resolution, higher FCR/CSAT, lower effort, and reliable containment.

WHO WE ARE:

Frontline Education is a pioneer of school administration software purpose-built for K-12 districts. We provide innovative, connected solutions for student and special programs, business operations, and human capital management with powerful data and analytics to empower educators and administrators. We earn the trust of K-12 leaders across the U.S. by serving as a consistently high-performing, forthright partner of school districts through every dimension of the company.
We’re a group of unique and talented individuals that love what we do. We’ve been lucky enough to land jobs with a rapidly growing tech company that supports an appreciative and friendly customer base. We work hard to make our customers happy, but we like to have a good time in the process. We are a company that strives to think in terms of “we” instead of “me.” We believe in the philosophy of servant leadership and that it’s all about putting others first. We also value the balance between family and work.
Frontline embraces diversity, equity, and inclusivity. We are intentionally building a workplace that respects, supports, and values the identities of all our employees. We believe this to be foundational in developing a strong community in our company. Frontline Education is an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

WHAT YOU BRING TO THE ROLE:

• Model customization (fine-tuning/LoRA) and synthetic data generation.
• Streaming and toolcalling/agents, structured outputs (JSON, function schemas).
• Cloud & MLOps: AWS (SageMaker/Bedrock/Lambda), Docker, Terraform, Kubernetes.
• Frontend integration patterns for AI UX (streaming UIs, fallbacks, user feedback loops).
• Domain experience in compliance-heavy environments (e.g., education, finance, healthcare).

THIS ROLE REQUIRES:

• 4–6 years in applied ML/AI or backend engineering with measurable production impact.
• Strong Python and software engineering fundamentals (testing, types, CI/CD).
• Practical LLM experience: OpenAI/Anthropic, or cloud providers (AWS Bedrock, Azure OpenAI, GCP Vertex).
• Experience with at least one deep learning or LLM framework (PyTorch, Transformers, vLLM) and one orchestration library (LangChain, LlamaIndex, Guidance, or custom).
• RAG and data pipelines: chunking/embedding strategies, vector DBs, metadata filtering, and document QA.
• Monitoring/telemetry for AI systems (e.g., MLflow, Weights & Biases, Prometheus, custom eval dashboards).
• Security & privacy awareness (PII handling, redaction, data retention).