Syndesus

Role Description A well-funded seed-stage startup building the next generation of autonomous trading technology. You are building the intelligence layer on top of a purpose-built execution system for AI agents operating with real capital around the clock. What You'll Own - Learning System & RL Loop (~70%): - Design and implement the pipeline that connects live trade outcomes back to strategy improvement — signal quality, position sizing, timing, risk parameters. - Build the evaluation framework that separates genuine predictive signal from noise across agents, market conditions, and configurations. - Automate the strategy generation and testing cycle — the system should explore new configurations, validate them against real fleet data, and surface deployment candidates. - Detect regime shifts in market conditions and adapt fleet behavior accordingly. - Decompose every trade into its component drivers — signal quality, execution efficiency, exit timing — and wire those attributions back into strategy design. - Manage fleet-level coordination: concentration risk, capital allocation, and the exploration vs. exploitation balance. - Build the telemetry and data capture layer that makes all of the above possible. - Model & Inference Infrastructure (~30%): - Own the build-vs-buy decision on model hosting — evaluate proxied external APIs versus fine-tuned models on owned infrastructure and execute the chosen path. - Determine whether domain-specific training on trading data meaningfully outperforms prompted general-purpose models — then build the pipeline to act on that answer. - Optimize inference for the specific demands of a large autonomous agent fleet: concurrent agents, structured outputs, cost efficiency at scale. - Build the agent telemetry layer capturing every decision, signal score, and evaluation across the fleet. Qualifications - A production closed-loop system — model outputs drove real-world actions, outcomes were measured, and that feedback automatically improved the next decision. - Practical RL or online learning experience — you understand the challenges of learning from real-world feedback rather than static datasets. - Full-stack ML ownership — you build the pipeline, deploy the model, and own the outcome; Python primary, comfortable with Go or TypeScript in production services. - High-stakes sequential decision-making domain experience — finance preferred but not required; robotics, autonomous vehicles, game AI, ad bidding, and supply chain all transfer. Nice to Have - LLM fine-tuning and open-source model serving in production (vLLM, TGI, PEFT/LoRA). - Multi-agent system design. - Financial ML — signal generation, execution optimization, portfolio construction. - Onchain or DeFi experience. Interview Process - Fast — target first call to offer within two weeks. - Intro call with founders (60 min) — fit, motivation, your closed-loop experience. - Technical deep-dive (60 min) — open-ended system design, no right answer, evaluating how you think. - Paid trial project (1 week, part-time) if needed — real problem, compensated.

Role Description We are seeking an experienced GPU Architect/Designer with strong expertise in shader core architecture and SIMT (Single Instruction Multiple Threads) execution models. This role involves defining next-generation GPU microarchitecture, optimizing throughput and efficiency, and driving scalable, high-performance parallel compute solutions. Key Responsibilities - Architecture & Microarchitecture - Define and evolve GPU shader core architecture, including SIMT execution units and pipeline design. - Design warp/wavefront scheduling, thread dispatch, and execution models. - Architect SIMT execution pipelines, including ALU pipelines, vector units, and control flow units. - Define thread divergence handling, reconvergence strategies, and branch control mechanisms. - Develop scalable shader architectures supporting high thread-level parallelism. - Collaborate on ISA definitions related to shader and compute workloads. - Analyze shader workloads and identify performance bottlenecks. - Optimize GPU execution efficiency across diverse workloads including compute shaders, AI/ML kernels, and high-performance parallel workloads. - Drive performance-per-watt and area efficiency improvements. - Memory & Interconnect - Define GPU memory subsystem interactions including register files, shared/local memory, L1/L2 cache hierarchy, and memory coalescing mechanisms. - Optimize memory access scheduling and bandwidth utilization. - Collaborate on interconnect and memory fabric architecture. - RTL & Design - Translate architectural specifications into microarchitecture definitions. - Implement shader pipeline logic in SystemVerilog. - Verification & Validation - Define architectural test plans and validation strategies. - Develop directed tests, constrained-random tests, and performance validation frameworks. - Analyze simulation and silicon results to drive design improvements. Qualifications - Education: Bachelor's, Master's, or PhD in Computer Engineering, Electrical Engineering, or Computer Science. - 10+ years of experience in GPU, CPU, or parallel processor architecture. - Strong experience with: - SIMT / SIMD architectures - Shader core design - Thread scheduling - Pipeline microarchitecture - Memory hierarchy design - Proficiency in: - SystemVerilog or Verilog - Microarchitecture specification development - Performance modeling tools - RTL-level debugging - Deep understanding of: - Parallel computing models - GPU execution models - Pipeline hazard handling - Synchronization primitives Compensation - 175,000 - 250,000 USD + Meaningful Equity

Role Description You'll operate at the intersection of hands-on engineering and senior technical leadership — owning architectural direction, writing production code, and tackling the kinds of complex problems that require both depth and creativity. Equally important is your ability to lead: mentoring engineers, aligning teams, and setting the technical bar across the organization. A central part of this role is driving the company's push into AI — embedding intelligent capabilities into the product and modernizing how the engineering team itself works. If you're someone who thrives in that space between builder and strategist, and wants to do it in a domain that genuinely matters, this is worth a conversation. What You'll Be Doing - AI Integration: Own the strategy and delivery of AI capabilities within the core product, while championing AI tooling adoption to improve how the engineering team builds software. - Domain Mastery: Build genuine depth across the product, the technical stack, and the broader AI ecosystem. - Architecture & Execution: Lead system design and contribute hands-on code for large-scale, complex, AI-enabled features. - Problem Ownership: Bring creative, pragmatic thinking to hard technical challenges with a clear focus on customer outcomes. - Collaboration: Work closely with cross-functional partners to drive alignment and move initiatives forward effectively. - Technical Governance: Shape and review architectural decisions to ensure consistency, scalability, and future-readiness. - Team Development: Give engineers clear, actionable technical feedback and actively raise the team's capability in modern AI engineering. Qualifications - 12+ years in software engineering, with 8+ years in a technical leadership capacity. - Demonstrated experience leading AI initiatives and shipping LLM or Generative AI features in commercial products; familiarity with AI-assisted developer tooling (e.g. Cursor, GitHub Copilot) is a plus. - Languages: Python, Java, JavaScript. - Frameworks: React, Vue, Flask, SpringBoot. Hands-on experience with orchestration frameworks like LangChain or LlamaIndex is a strong differentiator. - Databases: Comfortable across MySQL, Oracle, Postgres, DynamoDB, and Firestore. Experience with vector databases is a meaningful plus. - Cloud: AWS and/or GCP. - Equally comfortable as the person writing the code and the person setting the direction — and able to move between those modes as the team needs. - Willing to do the unglamorous work that keeps a product healthy, not just the high-profile stuff. - The kind of engineer others seek out — trusted for your technical judgement, approachable in how you share it. - Consistently spots opportunities to do things better and follows through with a concrete plan. - Takes ownership of raising the bar for engineering practice across the organization. - Can translate complex technical concepts clearly for both engineering and non-technical audiences. - Strong at assessing new and emerging technologies objectively, particularly in the fast-moving AI space.

Job Description: The IAM Service Manager is responsible for ensuring the reliable, secure, and efficient delivery of Identity and Access Management (IAM) services across the enterprise. This role combines service management discipline with strong technical understanding of IAM platforms, processes, and integrations. The ideal candidate is not just operationally strong, but also technically proficient in how IAM solutions function—including identity lifecycle management, authentication, authorization, federation, and privileged access controls. This role serves as the bridge between business stakeholders, support teams, and IAM engineering teams to ensure seamless service delivery. This is not a people management role—it is a hands-on service management role requiring IAM domain expertise. Key Responsibilities - IAM Service Delivery & Operations - Own day-to-day service delivery for IAM platforms, including Identity Governance, SSO, MFA, and Privileged Access Management (PAM) - Ensure all IAM-related tickets (access requests, provisioning, authentication issues, policy changes) are triaged, prioritized, and resolved within SLA - Monitor IAM service health, availability, and performance across platforms - Technical Oversight (IAM-Focused) - Maintain working knowledge of leading IAM tools such as: - Okta, Azure AD (Entra ID), Ping Identity (SSO/Federation) - SailPoint, Saviynt (IGA) - CyberArk, HashiCorp Vault, BeyondTrust (PAM) - Understand and oversee: - Identity lifecycle management (Joiner/Mover/Leaver processes) - SAML, OAuth, OIDC authentication flows - Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) - Partner with IAM engineers to coordinate deployments, upgrades, and integrations with enterprise systems (HRIS, AD, cloud platforms) - Incident, Change & Request Management - Oversee incoming IAM-related tickets and service requests, ensuring proper routing to IAM SMEs - Escalate high-priority incidents such as authentication outages, access failures, or security risks - Initiate and manage RFCs for IAM changes (e.g., policy updates, onboarding new applications, MFA changes) - Coordinate IAM patching, upgrades, and maintenance windows - Metrics, Reporting & Compliance - Track and report on IAM-specific KPIs: - SLA adherence for access requests and incident resolution - Provisioning/deprovisioning timelines - MFA adoption and authentication success/failure rates - Provide executive-level reporting on IAM service performance, risks, and trends - Support audit and compliance initiatives (SOX, ISO, SOC2) by ensuring proper access controls and documentation - Documentation & Continuous Improvement - Ensure IAM runbooks, architecture diagrams, and operational documentation are current and accessible - Analyze ticket trends to identify systemic IAM issues (e.g., provisioning failures, misconfigured roles) - Partner with engineering teams to drive automation and reduce manual access management processes - Support creation of end-user documentation for IAM services (e.g., MFA enrollment, password reset, access requests) - Collaboration & Coordination - Act as liaison between IAM engineering, security, helpdesk, and business stakeholders - Coordinate with helpdesk teams to ensure proper triage of IAM-related issues - Maintain on-call schedules for IAM support coverage Required Qualifications - 5–7+ years of experience in enterprise IT, with strong exposure to IAM operations and service delivery - Hands-on familiarity with one or more IAM platforms (e.g., Okta, Azure AD, SailPoint, CyberArk) - Solid understanding of: - Identity lifecycle management - Authentication protocols (SAML, OAuth, OIDC, LDAP) - Access control models (RBAC/ABAC) - Experience managing SLAs, ticket queues, and operational metrics in an IAM environment - Strong communication skills with the ability to translate technical IAM concepts to non-technical stakeholders - Experience with tools such as: - ServiceNow or similar ITSM platforms - Microsoft Project, PowerPoint, SharePoint - GitHub (or similar) for documentation and artifact management Preferred Qualifications - Experience supporting IAM in cloud environments (Azure, AWS, GCP) - Familiarity with compliance and audit frameworks (SOX, HIPAA, ISO 27001, SOC2) - Exposure to automation and scripting (PowerShell, Python) for IAM processes - Understanding of Zero Trust security models

Role Description We are looking for a Marketing Operations & Execution specialist to help operationalize and execute marketing initiatives for a fast-moving early-stage technology company. This role focuses on translating marketing plans into consistent execution across events, content distribution, webinars, and community engagement. The Marketing Operations Specialist will work closely with the Founding Marketing Lead and the founder to ensure that marketing initiatives move from ideas into real activity in the market. Key Responsibilities - Coordinate and execute marketing initiatives including webinars, virtual events, and campaign activities. - Manage the publishing and distribution of content across LinkedIn, newsletters, and other channels. - Support conference participation, speaking opportunities, and meeting scheduling around industry events. - Assist in expanding the founder’s professional network through structured engagement and outreach. - Maintain marketing calendars, event timelines, and campaign coordination. - Monitor and engage with discussions related to AI hiring, interview fraud, identity verification, and remote work security. Qualifications - 3–5 years of experience in B2B marketing operations, marketing coordination, or campaign management. - Experience working in SaaS or startup environments. - Highly organized and comfortable managing multiple initiatives simultaneously. - Strong execution mindset and attention to detail. - Interest in technology, AI, hiring, or security-related topics.