• Define and manage program schedules, deliverables, and turning points • Translate customer requirements into actionable tasks for all functional teams • Provide horizontal leadership to drive cross-functional program execution • Act as the primary customer interface, facilitating program kick-offs • Drive program execution from design through production deployment • Provide ongoing post-deployment sustaining support • Proactively communicate program health, risks, and key issues

• Lead the migration from a legacy Okta instance to the Compass Okta environment, including relationship, configuration, application, security, and operational transition workstreams • Develop and manage the end-to-end migration plan, including scope, milestones, dependencies, risks, communications, cutover planning, and stabilization activities • Coordinate detailed functional and technical plans across information security, infrastructure, application, product, technology operations, and business teams • Identify cross-functional interdependencies and establish prioritization to minimize disruption to daily operations • Track progress, drive accountability, resolve blockers, and ensure clear ownership across teams and workstreams • Evaluate technical and security risks related to Okta configuration, integrations, application access, user lifecycle management, policies, and operational readiness • Partner with security teams to ensure enterprise security controls, access policies, risk management expectations, and compliance needs are addressed throughout the migration • Collaborate with infrastructure and cross-functional groups to ensure the migrated Okta environment is scalable, efficient, supportable, and aligned to enterprise architecture standards • Manage communication with key stakeholders, including executive-level updates, team-level reporting, decision narratives, risk summaries, and issue escalation • Use data, metrics, and well-written narratives to create clarity, support decision-making, and communicate program health • Drive operational process improvements related to identity management, access administration, SaaS governance, support workflows, and technology operations • Build SOPs and reusable operating procedures to standardize and scale post-migration technology operations • Support full lifecycle program execution from kickoff through implementation, cutover, adoption, stabilization, and handoff • Ensure migration plans account for business continuity, user impact, application dependencies, security posture, and long-term operational support • Help Compass improve execution, efficiency, consistency, and governance across high-impact technical programs

• Manage the execution and communication of major, high-stakes cross-functional programs that require end-to-end alignment across the entire organization. • Develop and maintain comprehensive technical roadmaps and tactical schedules, balancing near-term delivery milestones with Stack’s long-term commercial autonomy vision. • Build deep, trust-based relationships with diverse cross-functional stakeholders to align engineering teams, push technical paths forward, and unify the organization around shared goals. • Analyze plans and requirements with engineering leads to uncover opportunities, challenge assumptions, and safely accelerate the development and deployment schedule. • Evaluate complex technical and resource trade-offs in constrained environments, framing clear choices and recommendations for leadership. • Synthesize granular technical progress into high-impact insights for senior leadership, delivering data-driven arguments that help executives make difficult decisions in reviews and all-hands. • Design and scale engineering processes within your programs, establishing operational frameworks that reduce friction and elevate efficiency across the broader organization. • Explore new, highly complex technical domains as needed, stepping in proactively to fill leadership, execution, or process gaps to ensure program success.

Role Description We are seeking a Tech Lead to lead our AI Inference team. In this role, you will bridge the gap between complex research and production-grade engineering, while cultivating a high-performing team culture. You will lead and grow a squad of 3 developers, balancing hands-on technical contribution with strong people leadership — setting direction, unblocking your team, and driving execution on high-performance systems that optimize Large Language Model (LLM) serving. The ideal candidate combines deep technical expertise in inference and scale with the leadership maturity to mentor, motivate, and develop engineers in the evolving ecosystem of serving frameworks like vLLM and LMCache. What You'll Work On - Lead & Own: Take end-to-end ownership of AMG's core inference infrastructure — from the NVMe Token Warehouse and GDS data paths to the vLLM/LMCache serving stack — driving technical decisions and delivery outcomes. - Technical Direction: Guide a team of engineers through design, implementation, and delivery of high-throughput, low-latency LLM inference systems, setting high standards for code quality, architecture, and reliability. - Build at Scale: Stay hands-on across the AMG stack (Python, C++, CUDA, vLLM, NIXL/Dynamo, Kubernetes), contributing directly to production systems while providing technical leadership to the team. - Solve Hard Problems: Tackle the real frontier challenges of inference engineering — disaggregated prefill/decode, persistent off-HBM KV caching, RDMA-based transport, and multi-tier GPU memory hierarchies — that define what's possible at scale. - Grow People & Teams: Mentor and coach engineers through regular 1:1s, career coaching, and sprint reviews. Foster a culture of ownership, collaboration, and technical excellence within the AMG team. - Stay on the Frontier: Track the evolving inference ecosystem, benchmark new tools (SGLang, TRT-LLM, NVIDIA Dynamo), and help the team make timely decisions about when to adopt, build, or pivot. Qualifications - 5+ years of professional software engineering, with proven experience leading engineers and owning complex production systems — ideally in AI/ML infrastructure or high-performance computing. - Hands-on expertise with LLM serving systems — KV cache reuse, disaggregated prefill/decode, continuous batching, and multi-tier GPU memory hierarchies (HBM → NVMe). Strong familiarity with vLLM, LMCache, NIXL/NVIDIA Dynamo, or similar frameworks. - Strong Python and C++ skills (Rust a plus), with a solid grasp of CUDA, GPU memory management, and high-performance I/O — including GPUDirect Storage (GDS), RDMA, and NVMe data paths. - Experience deploying and scaling GPU workloads on Kubernetes, with familiarity in RDMA networking, bare-metal GPU clusters (H100/A100), and high-throughput distributed storage. - Demonstrated ability to mentor and develop engineers — running effective 1:1s, supporting career growth, and balancing technical execution with long-term team health. - A strong sense of engineering craftsmanship, with a track record of building reliable, high-throughput systems and continuously improving engineering practices. Benefits - Medical, Dental, Vision, Life Insurance - 401(K) - Flexible Time off (FTO) - Sick time - Leave of absence as per the FMLA and other relevant leave laws Company Description WEKA is an equal opportunity employer that prohibits discrimination and harassment of any kind. We provide equal opportunities to all employees and applicants for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.