Senior AI Engineer

Description

Sr. AI Engineer

Location : This position can sit remotely (in the US) or hybrid to Wayne, PA or Naperville, IL. .

How You'll Contribute to Our Mission

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.

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.

How You'll Drive Success

Own end-to-end development of LLM features : problem framing, data prep, prototyping, offline / online evaluation, deployment, and monitoring.

Build retrieval-augmented generation (RAG) pipelines with vector search (e.g., FAISS, Pinecone, OpenSearch / KNN) and document orchestration.

Implement prompt strategies, tool use / function calling, and guardrails for safety, bias, and privacy.

Integrate models in production services (REST / GraphQL / gRPC), including auth, rate limiting, and observability.

Stand up evals and experiment frameworks (A / B tests, golden sets, regression suites) with clear success metrics.

Optimize for latency, cost, and quality : prompt compression, caching, model selection, fine-tuning / LoRA, distillation where appropriate.

Collaborate with DevOps / MLOps / Platform to automate CI / CD, data / version management, and feature flags.

Embed with CX / Support to mine tickets, chats, and call transcripts; convert VOC into training / eval datasets and backlog priorities.

Instrument user journeys and define online / offline evals (win rate, hallucination rate, TTR, CSAT / NPS); run A / B tests and ship iterative improvements.

Build feedback loops (thumbs-up / down, rationale capture, escalation) and human-in-the-loop fallbacks that protect quality.

Own reliability and UX details that matter for customers : latency budgets, safe fallbacks, clear handoff to human agents, accessibility.

Partner with Trust / Legal / Security to ensure privacy-by-design and compliant data handling; implement guardrails and red-team mitigations.

Success looks like (first 6 months) :

Document designs and teach best practices to engineering partners.

Ship 1–2 LLM features to production with SLAs, monitoring, and rollback plans.

Establish an eval harness (offline + online) and quality gates for prompts / RAG.

Reduce average latency / cost per request by ≥20% without quality regression.

Create internal runbooks and dashboards for reproducibility and troubleshooting.

What You Bring to Help Us Grow

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).

What You'll Need to Thrive

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).

Tools you may use :

Python, PyTorch, Hugging Face, vLLM, LangChain / LlamaIndex, FAISS / Pinecone / OpenSearch, Postgres, Redis, Docker, Terraform, GitHub Actions, MLflow / W&B, AWS (Bedrock, SageMaker, Lambda, S3, CloudWatch).

Our Mission, Our People, Our Purpose

At Frontline Education, we’re reimagining what’s possible by becoming an AI-first organization, transforming how we think, work, and serve the educators who shape our schools every day. By using AI in thoughtful, practical ways, we’re creating tools that help educators save time, gain insights, and focus more on what matters most — their students.

As part of our team, you’ll be expected and empowered to build and apply AI skillsets that grow with you, because at Frontline Education, technology amplifies what matters most : the human drive to learn, improve, and make a difference.

How We Support Growth, Balance, and Well-Being

Personalized Time Off : Take time when it’s needed most — whether that’s a family vacation, a reset day, or simply time to rest and refocus.

Paid Sick Time : Separate, dedicated sick leave to care for yourself or loved ones.

Volunteer Time Off : Paid time to give back and support causes that matter to you.

Ten Paid Holidays : Enjoy meaningful moments and traditions throughout the year.

Our Philosophy : We believe time away from work helps you bring your best self to it.

Continuous Learning and Growth

World-Class Learning Access : Explore thousands of on-demand courses through platforms like LinkedIn Learning.

Leadership & Technical Skill Building : Develop new capabilities and chart your own professional path.

AI Empowerment : Use OpenAI tools to build fluency with emerging technology and harness AI as a creative partner for innovation and problem-solving.

Tuition Reimbursement : Invest in formal education to advance your skills and career.

Ongoing Learning Culture :  Participate in company-led webinars on AI, inclusion, and industry trends—designed to inspire curiosity and continuous improvement.

Health, Happiness, and Purpose

Wellness Initiatives : Company-sponsored programs that support physical, mental, and emotional well-being.

Employee Assistance Program (EAP) : Confidential support for you and your family’s needs.

Comprehensive Benefits : Health and financial benefits that support your happiness and future.

A Culture That Cares : At Frontline Education, we want every team member to learn, grow, and thrive—personally, professionally, and purposefully.

Compensation & Benefits

Salary Range : $135,000 - $150,000 per year (based on experience, skills, and internal equity).

Bonus eligibility, 401(k) match, ESPP, comprehensive health benefits.

Personalized PTO and tuition reimbursement for eligible coursework.

Inclusion, Belonging & Equal Opportunity

Frontline Education is an equal opportunity / affirmative action employer. We aspire to have an inclusive workplace and strongly encourage suitably qualified applicants from a wide range of backgrounds to apply and join our team.

Interview Process & Data Privacy

As part of our interview process, Frontline uses video conferencing tools that include photo capture and may include automated transcription features. A screenshot or photo will be taken at the start of the interview for internal identification and record-keeping purposes only, and transcription may be used to support notetaking and evaluation consistency. These materials are used solely by our recruiting and hiring teams, stored securely, and not shared outside the hiring process. Candidates may opt out of the transcription at any time by notifying their recruiter in advance. Frontline processes this information in accordance with applicable data privacy laws and only for legitimate business purposes related to recruitment and hiring.

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