Role Description Do you want to empower organizations to build smarter compensation strategies while ensuring fair pay for all employees? Syndio is the leading pay governance and compensation intelligence platform. We help organizations make better pay decisions at every stage of the compensation lifecycle, from leveling and offers to promotions and merit. Our platform gives HR, compensation, and finance leaders the data and decision support they need to govern pay fairly, compliantly, and with confidence. Join us in our mission to help companies make smarter pay decisions they can trust! About the Role Syndi is Syndio's AI platform — one shared agent experience (in-product chat, Slack, Teams) serving our product lines, built on syndi-api: an agent runtime owning orchestration, tool calling, memory, RAG, evals, and observability, live in production today. The platform is young (v1 shipped this quarter), moving fast, and designed around a clear operating model: product teams contribute domain content through APIs, evals, and knowledge — the platform owns the experience. We're hiring a staff-level engineer to take ownership of major runtime surfaces and grow into a technical owner of the platform. This is a high-autonomy role on a small team (3–4 engineers): you'll design, ship, and operate systems end-to-end, and you'll work directly with product-team owners through the platform's contribution seams. What You'll Work On - Core runtime surfaces of syndi-api: the agent loop, tool execution and registry, memory, context management (Python, Postgres, Claude on Vertex, GCP). - The eval system — offline gates and online detector/judge evals written onto production traces — and its growth as product teams adopt it. - Production operation: observability (Datadog LLM Obs), incident response, the reliability of an agent surface real customers use. - The platform's contribution seams: reviewing product teams' tool wrappers and evals, evolving the GET /tools registry and drift-detection contract. - Clarifying, designing, and implementing compliance and legal requirements for Syndi. Qualifications - 5+ years building production backend systems; deep comfort with Python, relational stores, and cloud infra (we're on GCP/Kubernetes). - You've built LLM-powered systems in production — an agent loop, tool-calling integration, RAG, or eval infrastructure — and have opinions from the scar tissue. - You design for operability: legal compliance, tracing, evals, and kill switches are part of the feature, not afterthoughts. - You can own a technical domain with light supervision: propose direction in writing with clear API specs, take review, ship, and carry the pager for what you shipped. - Strong written communication — our operating model runs on design docs and PR review across team boundaries. Nice to have - Experience being the platform side of a platform/product relationship. - SSE/streaming systems. - Compliance-adjacent engineering (data minimization, auditability). - Prior Staff scope. Benefits - 💰 Competitive Compensation. For this role our salary is targeted at $205-225k USD or $180-200k CAD per year. Final offer amounts are determined by factors such as experience and expertise. - 🏆 Syndio Equity. So you can share in Syndio’s success. - 🏝 Flexible Vacation Policy. We encourage our team to recharge when they need to (up to 20 days PTO in Canada) plus paid sick & safe time, compassion leave, and voting leave. - 🩺 Medical, Dental, Vision. Syndio pays 90% of employee premiums, and 50% for dependents. - 🏥 Life Insurance & Disability. Syndio covers the full premium. - 📍Remote-first in US + Alberta; in Calgary, non-mandatory office available #LI-Remote. Role Progression - First 30 days: Focus on onboarding, mastering our core agent runtime surfaces, and shipping a small-scale contribution to understand the platform's contribution seams. - First 60 days: Independently manage core runtime surfaces, troubleshoot complex issues, and start co-owning a consumer team's integration from API design to eval sign-off. - First 90 days: Concretely ship a major runtime capability end-to-end (e.g., multimodal input or a new channel surface), take on-call for the platform, and co-own a consumer team's integration from API design to eval sign-off. The interview overview Below you'll find an outline of the interview plan for our Senior Software Engineer (AI Platform) position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision. - Recruiter Screen (25 min) - Hiring Manager Interview (30 min) - Technical Evaluation - Design Skills (60 min) - Crossfunctional Team Interviews (2 x 30 min) At Syndio, we're building a diverse team that values candor, curiosity, and community. If you share these values and are interested in joining us, we'd love to talk with you even if you don't 100% meet the "about you" listed here. We don't expect anyone to have all the answers, as long as you're willing to learn and grow with us. Syndio is an Equal Opportunity Employer. We are building an inclusive and collaborative workplace as we grow, and we welcome team members regardless of gender/identity, sexual orientation, race or cultural background, religion, physical disability and age.

• Drive AI Adoption and Practical Enablement Deliver hands-on AI workshops, coaching sessions, office hours, and enablement experiences for employees at varying levels of AI confidence. • Reinforce responsible use, critical judgment, output validation, and appropriate escalation when AI-generated content may affect customer, business, risk, or financial outcomes. • Translate technical AI concepts into clear, practical language for non-technical audiences. • Use real business examples, demonstrations, and hands-on practice to help employees build confidence. • Create psychologically safe learning environments for employees who feel hesitant, overwhelmed, skeptical, or unsure where to begin. • Design, update, and maintain AI enablement materials, job aids, quick reference guides, workshop decks, videos, resource pages, and practical toolkits. • Partner with learning, communications, operations, and business stakeholders to create role-based learning paths and practical resource experiences. • Support workshop operations, including intake, scheduling, participant communication, follow-up, feedback collection, and reporting. • Track Measurement, Adoption, and Value Support reporting on adoption metrics, usage trends, workshop participation, training completion, feedback, user needs, and business impact. • Leverage data to identify power users, low-adoption areas, skill gaps, and opportunities for targeted enablement. • Translate usage data and feedback into practical recommendations for leaders. • Help define success measures for pilots, learning initiatives, resource pages, workflow enablement, and AI adoption programs. • Support Change Management and Leader-Led Adoption Help managers understand how to guide their teams through AI adoption with clarity, confidence, and responsible expectations. • Help surface adoption barriers such as fear, lack of confidence, unclear expectations, workflow fit, trust concerns, or lack of time. • Partner with stakeholders to turn those barriers into better communications, better resources, and more targeted support. • Contribute to AI Enablement Strategy Stay current on emerging AI capabilities, new Copilot features, agent experiences, prompt strategies, and practical enterprise AI use cases. • Identify opportunities to improve training, resource design, adoption strategy, measurement, and enablement operations. • Bring structured recommendations to help the team prioritize high-value AI opportunities. • Help ensure AI enablement efforts are scalable, reusable, measurable, and aligned to business priorities. • Act as a business-facing bridge between users, leaders, technical teams, product teams, learning teams, and enterprise AI partners.

• Design, build, and deploy core application components of EVERSANA’s AI Agency Platform. • Develop backend services, APIs, and front-end interfaces integrating seamlessly with third-party systems. • Collaborate with AI/ML Engineers to integrate model endpoints (LLMs, RAG systems, Vertex AI Agents). • Build microservices and APIs supporting multi-tenant scalability. • Automate deployments using CI/CD pipelines and collaborate with DevOps on containerization and orchestration.

• Maintain deep expertise in one or more AI technology areas. • Clearly present and communicate relevance of technological advances as relevant to our work in biostatistics, bioinformatics and data science at Exact Sciences. • Develop perspectives on “AI technology affordance”: what do these advances in AI technology allow us to do (more efficiently and / or more effectively) that we couldn’t do before. • Work with stakeholders to discover and refine requirements for ML- and AI-based solutions to business problems with a focus on bioinformatics, biostatistics and data engineering applications. • Collaborate with other ML/AI engineers and relevant partners to design software solutions that utilize state-of-the art artificial intelligence and machine learning techniques. • Work with other AI and ML engineers and software engineers to implement and deploy ML and AI solutions. • Work in an Agile framework focused on iterative, rapid delivery of proof-of-concept solutions. • Contribute to the development of an AI strategy at Exact Sciences that empowers the team to leverage both existing AI and ML tools and those developed in-house to accelerate and enhance bioinformatics, biostatistics and data science processes and outcomes. • Contribute to internal initiatives to build training resources, develop knowledge bases, and educate on advanced AI and ML technologies and best practices for leveraging them. • Provide mentorship and coaching to more junior level team members. • Act as resource and subject matter expert in core team and/or cross-functional meetings. • Exercise discretion and judgment within broadly defined practices and policies in selecting methods and techniques and evaluation criteria for obtaining and interpreting results. • Ability to apply strong communication skills and to explain difficult, sensitive, and/or complex information to audiences of peers. • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork. • Support and comply with the company’s Quality Management System policies and procedures. • Maintain regular and reliable attendance. • Ability to act with an inclusion mindset and model these behaviors for the organization. • Ability to work designated schedule. • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 85% of a typical working day. • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.