> Markdown version of [/jobs/ext/183859-sr-software-engineer-go-to-market-ai-team](https://www.wearedevelopers.com/jobs/ext/183859-sr-software-engineer-go-to-market-ai-team). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Software Engineer (Go-To-Market AI Team) - **Company:** Frontline Education - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $120,000.0 - $135,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Program Optimization, Continuous Integration, Data Cleansing, Data Governance, Monitoring of Systems, Python (Programming Language), Machine Learning, Metadata, Regression Testing, Prometheus, Search Technologies, Pytorch, Deep Learning, Caching, Kubernetes, Low Latency, HuggingFace, Graphql, Machine Learning Operations, Front End Software Development, Functional Programming, Terraform, Software Version Control, Docker - **Published:** May 22, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=79da7babfe0a8608 ## About the Role Do you have experience in gRPC?, * 5-7 years of experience in backend engineering, applied machine learning, or intelligent systems development with demonstrated production impact across customer-facing or operational business environments. * Strong software engineering fundamentals including Python development, testing practices, CI/CD workflows, and maintainable system design. * Experience integrating foundation model APIs and cloud-based inference platforms such as AWS Bedrock, Azure OpenAI, or Google Vertex AI. * Hands-on familiarity with deep learning and inference tooling including PyTorch, Hugging Face Transformers, or vLLM. * Experience building search and retrieval pipelines including embeddings, vector databases, metadata filtering, and document question-answering workflows. * Knowledge of observability, telemetry, and monitoring tools such as MLflow, Weights & Biases, Prometheus, or custom evaluation dashboards. * Understanding of security, privacy, and responsible data handling practices including PII protection, redaction, and retention considerations. * Experience working in collaborative, cross-functional environments where communication, adaptability, and ownership are highly valued. Additional experience that may help you stand out: * Exposure to streaming architectures, structured outputs, function calling, or agentic workflows. * Experience with cloud and infrastructure technologies such as Docker, Terraform, Kubernetes, SageMaker, Lambda, or AWS-native tooling. * Familiarity with frontend integration patterns for intelligent user experiences including streaming interfaces and feedback loops. * Experience working within highly regulated or compliance-focused industries such as education, healthcare, or finance. What you'll need to thrive * A growth mindset and curiosity about how AI and emerging technologies can create better experiences for users and teams. * The ability to balance innovation with thoughtful execution, reliability, and customer trust. * Strong collaboration skills and a willingness to partner across teams to solve meaningful problems together. * Comfort navigating ambiguity, experimenting responsibly, and continuously improving through feedback and learning. * A customer-centered approach that focuses on outcomes, usability, and long-term value rather than simply delivering features. * A proactive, accountable mindset that embraces ownership and follows through on commitments. * An interest in applying AI thoughtfully to business operations, customer engagement, and revenue-focused workflows in ways that create meaningful outcomes for teams and customers. * A passion for building technology that helps educators, students, and communities succeed. ## Description We are looking for a Senior Software Engineer who is passionate about building intelligent, production-grade experiences that help solve meaningful challenges at scale. In this role, you will design and deliver AI-enabled solutions that learn, search, reason, and adapt using real-world data while maintaining a strong commitment to reliability, safety, and customer impact. As part of Frontline's Go-To-Market AI team, you'll help build intelligent solutions that support how Frontline engages, supports, and grows relationships with customers across the full customer lifecycle. This team partners closely with Sales, Customer Success, Support, Marketing, Revenue Operations, and other customer-facing teams to improve workflows, uncover insights, streamline operations, and create more personalized and effective customer experiences through thoughtful application of AI. You'll work cross-functionally with product, platform, data, and business teams to turn complex operational and customer-facing challenges into practical, measurable solutions that improve outcomes for both internal teams and the educators and school communities we serve. This role is ideal for someone who thrives in fast-moving environments, embraces curiosity and experimentation, and takes ownership from idea through deployment. As part of Frontline's AI-first transformation, you'll help shape how intelligent systems are responsibly integrated into business processes, customer experiences, and internal workflows while keeping people, trust, usability, and customer success at the center of every decision. How you'll drive success You'll help the Go-To-Market organization scale customer impact by building intelligent systems and AI-enabled workflows that improve operational efficiency, decision-making, and customer experiences across revenue and customer-facing teams. * Own the end-to-end development lifecycle for intelligent product capabilities, including discovery, data preparation, prototyping, evaluation, deployment, monitoring, and optimization. * Build semantic search and intelligent retrieval systems using modern vector databases and retrieval orchestration frameworks such as FAISS, Pinecone, OpenSearch/KNN, LangChain, or LlamaIndex. * Build intelligent search, knowledge retrieval, and workflow automation capabilities that help customer-facing teams access insights, respond faster, and work more effectively. * Design scalable inference strategies, integrations, and safeguards that promote reliability, reduce bias, protect privacy, and support responsible AI usage. * Integrate intelligent models into production-grade services using REST, GraphQL, or gRPC architectures with strong attention to observability, authentication, and operational resilience. * Create experimentation and evaluation frameworks including A/B testing, regression testing, offline evaluation, and quality measurement pipelines that support confident decision-making. * Optimize systems for latency, cost, scalability, and quality through thoughtful architecture decisions, caching strategies, model selection, fine-tuning, and performance improvements. * Partner with MLOps and Platform Engineering teams to strengthen CI/CD automation, infrastructure reliability, feature flagging, and version management practices. * Collaborate cross-functionally to solve customer-centered problems and ensure solutions are practical, measurable, and aligned to business outcomes. * Document technical designs, share best practices, and contribute to a culture of continuous learning and knowledge sharing. * Contribute to an engineering culture grounded in accountability, collaboration, innovation, and a commitment to delivering meaningful value for customers. Success in this role may include: * Delivering intelligent features and workflow capabilities into production that improve customer-facing operations with clear SLAs, monitoring, rollback strategies, and measurable business impact. * Establishing evaluation frameworks and quality gates that improve reliability and reproducibility across inference and retrieval systems. * Improving platform performance, operational scalability, and team efficiency while maintaining strong user and customer experiences. * Creating operational runbooks, dashboards, and engineering standards that help teams move faster with confidence. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [HTTP headers that make your website go faster](https://www.wearedevelopers.com/videos/1676-http-headers-that-make-your-website-go-faster) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Event based cache invalidation in GraphQL](https://www.wearedevelopers.com/videos/433-event-based-cache-invalidation-in-graphql) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)