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Do you want to impact the way millions of students experience education and learning? Come join Savvas - the number one provider of core curricula in the country. Savvas Learning Company is the industry leader in delivering the highest-quality educational materials. Savvas’s flagship K-12 solution Savvas Realize, is one of the edtech industry’s most versatile learning management systems (LMS), and was honored in both the primary and secondary education categories as a technology solution that is key to helping schools transition to remote, hybrid, and blended learning environments.  You will be part of an exciting team and work on products that are used by students every day. We are looking for engineers who are passionate about building innovative applications of the highest quality, realizing real value from AI and demonstrating ownership of the product area assigned to them.

Responsibilities

• Partner with business stakeholders to translate product vision into technical and data requirements for AI-powered solutions, advising on what's achievable, what's risky, and what requires further investigation.

• Own LLM application engineering (prompting + RAG + tool use + evaluation + guardrails + orchestration) as a core technical discipline, driving iterative optimization in partnership with subject matter experts.

• Define and oversee evaluation frameworks for AI-powered features, coordinating with subject matter experts to ensure inference quality, safety, and alignment with pedagogical standards

• Evolve production monitoring and regression testing for inference quality, cost, and latency, driving iterative improvements post-release.

• Evaluate emerging technologies and drive adoption of best-in-class tools and frameworks, incorporating their capabilities into the platform.

• Lead a globally distributed team and drive sound engineering design, implementation, quality, deployment and monitoring practices on AI-powered microservices and products.

• Architect distributed systems to ensure high availability, low latency, and fault tolerance.

• Leverage AWS services such as Bedrock, Lambda, ECS, DynamoDB, RDS, and S3 to build cloud-native solutions.

• Enforce security best practices across the codebase and AWS infrastructure, implementing defense-in-depth strategies and driving timely risk mitigation and remediation of vulnerabilities.

• Drive code automation practices across the team to ensure maintainability and extensibility

• Maintain hands-on involvement through prototyping, POCs, and direct contribution to critical implementations.

• Provide technical mentorship to engineering teams and conduct code and architecture reviews.

• Contribute to the organization's AI Center of Excellence by developing reference implementations, documentation, and best practices, while tracking the evolving AI landscape and identifying the right moments to introduce new capabilities.

• Collaborate with cross-functional teams, including frontend engineers, product managers, and operations teams, to align on technical solutions.
  

Qualifications

• Master’s or Bachelor’s degree in Computer Science or equivalent experience, with strong fundamentals and problem-solving skills

• We are looking for people with a long track record of success in delivering high-quality software. For this role, you should have at least 8 years of experience in software development roles and five years of experience working in an agile environment.

• We are seeking a candidate with 2+ years of experience with LLMs/generative AI applications, including production deployment experience.

• We need someone with a track record of balancing innovation speed with production reliability

• Three years of Python development experience is required, along with experience shipping Node-based services and/or modern web frontends (Angular preferred).

• We run a distributed microservices-based architecture in the cloud focused on APIs and event-driven design. Experience in deploying and maintaining production software in AWS is required.
  

Skills

• Software Design, Implementation (i.e., coding), and Testing.

• Solid understanding of ML/AI data practices: dataset curation, validation, and evaluation design.

• Experience with agent architectures, RAG, and tool-use patterns in production LLM applications is a plus.

• Proficient in database development in relational and NoSQL, Postgres and Amazon DynamoDB preferred.

• Understanding of Cloud Architecture and experience working with AWS resources, including cloud networking and security fundamentals.

• Strong, creative problem-solving and troubleshooting skills are a must, as is the ability to coach junior team members in these areas with proven ability to drive adoption of new processes and tools.

• Must assimilate information, distill knowledge, apply experience, and provide solution alternatives and recommendations.

• Must have strong time management skills - including the ability to work well under pressure, plan, set priorities across multiple projects, adapt to change, and meet established timelines.

• Effective written and verbal communication skills.

• AWS certification is a plus (Cloud Practitioner or higher)

• Experience in education technology or other high-stakes domains is a plus.