Do you remember the first time you deployed an Apache Cassandra cluster with Chef or Puppet? Did you realize that the world had changed and you were never deploying by hand again? When AWS suffers a regional outage of DynamoDB, do you immediately think about resiliency and replication lag? Do you understand how your services respond to these incidents? How did you feel when you first used Claude Code or Cursor to open a PR? Did you realize that you should never be without that rapid feedback and iterative power again? At C1, we know that the world has been transformed yet again and we never want to go back. We're building AI tools and we're building with AI tools—every day. We ship fast and we ship constantly. The hard problems are still hard, but the pace at which we can attack them has changed forever. We are looking for exceptional Staff and Principal Engineers to join our Functions team in New York. You'll be one of the first engineers in our new NYC office—helping establish the culture, hiring bar, and technical direction from day one. We want high-agency engineers who are excited to build an AI-native product using AI-native tooling. These are senior technical leadership roles crucial to driving our technical strategy, mentoring teams, and delivering complex, high-impact projects. If you bias toward action and care deeply about shipping, we want to talk to you. Here are a few blog posts highlighting how we approach hard problems: - Incremental Sync: How C1 Keeps Identity Data Fresh in Real Time - Building Trust Through Connector Reliability About C1 C1 is the first AI-native identity security platform that protects every identity: human, non-human, and AI. We make it possible for enterprises to move beyond the limitations of legacy identity governance—reducing their attack surface while actually improving the experience for everyone involved. Forward-thinking companies like DigitalOcean, Instacart, Ramp, and Zscaler trust C1 to secure their identities. We're backed by top investors and growing fast, but we're still small enough that every engineer shapes the product and culture. What You'll Do - Own the Automations platform end-to-end—from the policy engine that evaluates rules to the execution framework that takes action across hundreds of integrated systems - Plan and drive large projects with incremental deliverables—you'll contribute to major architectural decisions, assess technical risks, and communicate tradeoffs across teams - Work directly with customers to understand complex requirements and resolve hard problems—the best solutions come from deep understanding, not guesswork - Set the bar for code quality—deliver code that's maintainable, well-tested, and sets the standard for the team - Be a stabilizing force when things are ambiguous—keep the team aligned on priorities and moving forward even when the path isn't clear - Mentor and elevate others—delegate effectively, trust people with real ownership, and help engineers around you grow What We're Looking For You Likely Have - A track record of delivering complex, multi-team projects—you've shipped systems that handle real scale, real failures, and real customers - Deep experience with Go or similar backend languages, with strong opinions on how to write maintainable, performant code - Strong systems thinking—you balance technical debt against feature velocity and make pragmatic tradeoffs - Demonstrated technical leadership—you've driven architectural decisions, built consensus across teams, and helped other engineers grow - High agency—you figure out what needs to be built, not just how to build what you're told. You move fast and unblock yourself. - Deep understanding of production environments—you know how to debug, monitor, and operate the systems you build - Experience with AI-assisted development (Claude Code, Cursor, Copilot, or similar)—you're already using these tools and excited about what's next - Clear, persuasive communication—you can explain complex technical concepts to diverse audiences and build alignment - Ego in check—you care about getting it right, not being right You Might Also Have - Experience building AI-native products—integrating LLMs into production systems, prompt engineering, retrieval-augmented generation - Experience with identity and access management systems (SCIM, SAML, OAuth, LDAP, or similar) - Background in building multi-tenant SaaS platforms with enterprise security requirements - Familiarity with workflow orchestration technologies (Temporal, Airflow, or custom implementations) - Contributions to open source projects or engineering communities How We Work - Ship, Ship, Ship—we bias toward action. We'd rather ship something and learn than debate endlessly. Iteration beats perfection. - Build with AI—we use AI tools daily to write code, review PRs, explore ideas, and move faster. If you're not excited about this, we're not the right fit. - Earn the Customer's Trust—we build for real problems, not hypothetical ones. We talk to customers constantly and take their security seriously. - Practice Compassionate Candor—we give direct feedback because we care about each other's growth. Ego takes a back seat to getting it right. - Be the Conductor—we take ownership of outcomes, not just tasks. If something needs doing, we do it. Hiring Philosophy We're looking for people with passion, grit, and integrity. We encourage you to apply even if your experience doesn't precisely match every requirement above. We welcome diverse perspectives and people who think rigorously and aren't afraid to challenge assumptions. ConductorOne is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

• Lead discovery workshops with business stakeholders to identify AI opportunities • Translate business problems into AI-driven solution approaches • Define pilot scope, success metrics, and value realization frameworks • Drive stakeholder engagement across business and technical teams • Present solution demos, insights, and outcomes to senior leadership • Collaborate with AI engineering teams to ensure alignment between business goals and technical execution

• Building the AI growth platform for real estate • Collaborate with cross-functional teams to deliver high-quality software solutions • Participate in product-oriented technical initiatives end-to-end

Role Description A self-motivated A-player who is results-oriented, operates at a fast pace, and takes pride in delivering high-quality, trustworthy AI systems; an experienced generative AI practitioner with deep expertise in LLM-based system design, including prompt engineering, RAG architectures, fine-tuning, and evaluation; highly focused on accuracy and reliability, with a clear understanding that hallucinations and misinformation erode user trust and equipped with concrete strategies to prevent them; proficient in building and maintaining end-to-end production ML pipelines, from data preparation through deployment and monitoring; and a strong collaborator who works effectively across engineering, product, and customer-facing teams in a fully remote environment. Essential Functions - Generative AI System Design & Development - Design, build, and continuously improve LLM-powered systems across Amira's product and operations — from internal tools to customer-facing features. - Own RAG pipelines end-to-end: document ingestion, chunking strategy, embedding selection, retrieval tuning, and response synthesis. - Develop and enforce guardrails, grounding strategies, and confidence thresholds to mitigate hallucination and ensure output reliability. - Architect prompt chains and agent workflows that are robust, maintainable, and cost-effective at scale. - Fine-Tuning, Evaluation & Continuous Improvement - Design and operate evaluation frameworks to measure system accuracy, helpfulness, hallucination rate, and task completion across generative AI features. - Fine-tune and adapt foundation models for domain-specific tasks, including data curation, training pipeline setup, and performance benchmarking. - Implement automated and human-in-the-loop review processes to catch and correct problematic outputs. - Monitor production traffic, identify failure modes, and iterate rapidly on retrieval, prompting, and generation strategies. - Integration & Infrastructure - Integrate LLM-powered features with internal systems and third-party platforms (e.g., Salesforce, CRM tools) via APIs, connectors, and data sync workflows. - Contribute to shared ML infrastructure and tooling used across Amira's AI systems. - Help explore and implement solutions that make generative AI economically viable within the budget constraints typical of public schools and education SaaS. - Cross-Functional Collaboration - Partner with learning design, content, product, and customer success teams to ensure AI systems are grounded in accurate, up-to-date domain knowledge. - Translate business needs into well-scoped generative AI solutions and communicate tradeoffs clearly to non-technical stakeholders. Qualifications - 2+ years of hands-on experience building and deploying LLM-based systems in production. - Deep familiarity with RAG architectures: embedding models, vector databases, retrieval strategies, and response grounding. - Demonstrated experience with evaluation and benchmarking of LLM outputs — including hallucination mitigation, confidence filtering, output validation, and fallback strategies. - Practical experience with prompt engineering, prompt chaining, and/or agent orchestration frameworks (LangChain, LlamaIndex, or similar). - Proficiency in Python and experience working with LLM APIs (open-source, Anthropic, OpenAI, etc.). - Experience building and maintaining ML or data pipelines in AWS or similar cloud infrastructure (Lambda, S3, RDS, etc.). - Degree in computer science or a related technical field, or equivalent practical experience. Preferred Qualifications - Experience fine-tuning foundation models or running RLHF / preference-based feedback loops for domain-specific improvement. - Experience in education SaaS or with education-sector customers (districts, schools, state agencies). - Familiarity with Salesforce or similar CRM platforms and their API/data ecosystems. - Experience with evaluation tooling, custom eval harnesses, or LLM-as-judge approaches. - Background working with conversational AI, chatbots, or customer-facing generative AI features. - Proven ability to operate in a fast-paced, goal-oriented startup environment and manage multiple concurrent workstreams. Benefits - Competitive Salary - Medical, dental, and vision benefits - 401(k) with company matching - Flexible time off - Stock option ownership - Cutting-edge work - The opportunity to help children around the world reach their full potential