Note: The job is a remote job and is open to candidates in USA. Frontline Education is transforming how schools operate to ensure the success of every educator and student. They are seeking multiple Senior Software Engineers to join their AI Enablement Platform Engineering team, where the focus is on building and evolving foundational AI capabilities that support product and platform teams across the organization.
Responsibilities
- Design, build, test, deploy, and support shared AI platform capabilities and operational AI services
- Develop orchestration services, integration layers, reusable APIs, workflow infrastructure, and platform services that accelerate AI adoption across Frontline
- Build platform capabilities supporting provider abstraction, governance controls, telemetry, observability, explainability, auditing, and policy enforcement
- Design and support distributed and asynchronous workflows leveraging event-driven architectures and messaging technologies such as Kafka
- Contribute to operational AI workflow patterns including orchestration, retrieval workflows, tool integration, asynchronous execution models, and agentic workflows
- Support modernization and evolution of AI platform capabilities as technologies, governance requirements, and business needs mature
- Contribute to monitoring, resiliency, incident response, troubleshooting, governance enforcement, and platform reliability initiatives
- Partner with downstream engineering teams to simplify AI adoption and reduce integration complexity
- Help build safe, governed, and trustworthy AI platform capabilities that support enterprise operational requirements
- Contribute to solutions that improve observability, explainability, auditing, telemetry, access controls, and responsible AI practices
- Partner with Security, Data Platform, Architecture, and Product Engineering teams to ensure platform capabilities align with organizational governance standards
- Help teams balance innovation, operational maturity, customer value, and risk management
- Support the development of reusable governance patterns that make responsible AI adoption easier across Frontline's ecosystem
- Participate in discovery, refinement, and design discussions to evaluate requirements, identify tradeoffs, and shape practical AI platform solutions
- Collaborate closely with Product Managers, QA Engineers, Security teams, Data Platform teams, Architects, Technical Leads, and Engineering Managers throughout the development lifecycle
- Contribute to architectural discussions while aligning solutions to platform standards, governance expectations, and long-term engineering objectives
- Communicate technical concepts, implementation approaches, operational considerations, governance implications, and platform adoption strategies effectively to both technical and non-technical audiences
- Build strong partnerships across geographically distributed and cross-functional teams
- Develop secure, scalable, maintainable, and high-performing platform solutions
- Contribute to automated testing strategies including unit, integration, workflow, operational, and evaluation testing
- Participate in code reviews and provide thoughtful technical feedback that improves engineering quality and consistency
- Support CI/CD automation and continuous delivery practices
- Contribute to improvements in observability, governance, resiliency, explainability, scalability, and developer productivity
- Promote reusable engineering approaches, platform consistency, and sustainable development practices
- Mentor fellow engineers and contribute to a culture of ownership, collaboration, and continuous learning
- Leverage modern AI-assisted development tools such as GitHub Copilot, Claude Code, OpenAI Codex, and emerging technologies to accelerate development, testing, troubleshooting, documentation, workflow development, and solution exploration
- Apply strong engineering judgment when evaluating and validating AI-generated outputs
- Use AI to improve productivity while maintaining high standards for governance, security, maintainability, scalability, explainability, and operational integrity
- Champion responsible and effective AI adoption across engineering workflows
- Help establish patterns that enable teams to confidently use AI while maintaining trust, reliability, and customer focus
Skills
- Bachelor's degree in Computer Science or a related field, or equivalent professional experience
- 5+ years of professional software engineering or platform engineering experience
- Experience designing and building cloud-native distributed systems
- Strong understanding of distributed systems, asynchronous workflows, API design, observability, operational telemetry, security concepts, and governance principles
- Experience building scalable platform capabilities that enable engineering teams to deliver solutions efficiently and reliably
- Familiarity with AI orchestration, workflow execution, integration patterns, and operational AI concepts
- Ability to independently design and deliver complex platform capabilities with high levels of quality, reliability, maintainability, and operational excellence
- Experience participating in technical design discussions and evaluating implementation tradeoffs
- Strong understanding of testing, scalability, governance, and software quality practices
- Experience mentoring engineers and contributing to engineering best practices
- Experience leveraging AI-assisted development tools to improve engineering productivity while applying sound judgment and validation practices
- Deep expertise designing, building, and evolving large-scale cloud-native platform capabilities that support AI, orchestration, governance, and distributed workflows
- Experience leading technical solutions that span multiple teams, platforms, or engineering domains
- Proven success influencing engineering standards, governance models, architectural decisions, and platform direction
- Strong systems-thinking capabilities with experience balancing innovation, scalability, explainability, governance, reliability, security, and customer outcomes
- Experience driving adoption of reusable platform capabilities across multiple engineering organizations
- Demonstrated success mentoring engineers and elevating engineering practices across broader teams
- Experience influencing technical strategy, platform modernization initiatives, AI enablement efforts, and long-term platform evolution
- Experience establishing effective AI-assisted engineering practices and helping teams adopt modern development workflows responsibly
- Ability to anticipate downstream impacts and guide engineering decisions that improve long-term platform sustainability, governance, and adoption
- Experience designing and building cloud-native distributed systems
- Strong understanding of distributed systems and asynchronous workflows
- Strong understanding of event-driven architectures
- Strong understanding of API and integration platform design
- Strong understanding of observability and operational telemetry
- Strong understanding of security and governance concepts
- Strong understanding of AI orchestration and workflow concepts
- Experience with AWS cloud-native services including Lambda, EC2, S3, SNS/SQS, Container-based workloads, AI or data-related services
- Experience with Kafka or equivalent messaging technologies
- Experience with Docker
- Experience with modern API and microservice architectures
- Experience with CI/CD pipelines
- Familiarity with operational AI patterns including orchestration, retrieval workflows, agentic execution models, provider abstraction concepts
- Experience working within Agile software development environments
- Strong communication, collaboration, and problem-solving skills
- Experience with AWS Bedrock or similar enterprise AI platforms
- Experience building shared platform capabilities consumed across multiple product teams
- Experience with observability, governance, auditing, or telemetry platforms
- Familiarity with vector search, embeddings, retrieval workflows, and AI integration patterns
- Experience supporting AI or agentic enablement in enterprise application environments
- Familiarity with Kubernetes or container orchestration platforms
- Experience working within multi-tenant SaaS environments
- Experience collaborating with geographically distributed engineering teams
- Experience leveraging AI-assisted or agentic development workflows in professional software engineering environments
Benefits
- Annual bonus opportunity.
- 401(k) with company match.
- Comprehensive medical, dental, and vision coverage.
- Employee stock purchase opportunities where applicable.
- Tuition reimbursement and professional development support.
- Flexible time off and wellness-focused benefits.
- 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.
- 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.
- Ongoing Learning Culture: Participate in company-led webinars on AI, inclusion, and industry trends—designed to inspire curiosity and continuous improvement.
- 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.
Company Overview
Frontline Education is an integrated insights software primarily focusing on human capital management. It was founded in 1998, and is headquartered in Malvern, Pennsylvania, USA, with a workforce of 501-1000 employees. Its website is http://www.frontlineeducation.com/.Company H1B Sponsorship
Frontline Education has a track record of offering H1B sponsorships, with 3 in 2023, 1 in 2021, 1 in 2020. Please note that this does not guarantee sponsorship for this specific role.