Technical Lead Manager

100% remote. Must reside in Bay Area.Must have prior Start Up experience.About the RoleWe're looking for a Tech Lead Manager (TLM) to own and drive the AI teambuilding the intelligence layer at the heart of our Client's platform. This is a hybridIC/management role where you'll spend approximately 70% of your time onhands-on technical work and 30% on people management and team leadership.On the technical side, you'll design, build, and ship the models, agents, and MLsystems that power Our Client's predictive and prescriptive capabilities"”fromforecasting workforce demand and flagging burnout risk to orchestrating LLM-driven planning workflows trained on each customer's historical data. You'll writeproduction code, drive architectural decisions across model training, serving, andTech Lead Manager, AI 1evaluation, and set the bar for applied ML quality. On the management side, you'llbuild, mentor, and grow a high-performing team of ML and AI engineers, owningtheir career development, performance, and day-to-day delivery.The ideal candidate thrives at the intersection of applied ML depth and peopleleadership"”comfortable context-switching between shipping models andcoaching engineers. You'll set the technical direction for your team, partnerclosely with Product, Design, and Data, and ensure your squad delivers AIcapabilities that are reliable, measurable, and shipped at a pace that matchesour Clients's growth trajectory.What You'll DoTechnical Leadership & Execution (~70%)Own the architecture and delivery of AI features end-to-end"”from dataingestion and feature engineering to model training, serving, evaluation, andthe product surfaces they power.Design and build the systems behind our Client's forecasting, recommendation,and agentic planning capabilities, including LLM-based pipelines, classical MLmodels, and hybrid approaches trained on per-customer historical data.Drive engineering excellence: lead architecture discussions for model trainingand inference infrastructure, set standards for offline/online evaluation,experimentation, and responsible AI, and participate in the full ML lifecyclefrom problem framing through deployment, monitoring, and on-call.Make pragmatic technical decisions that balance model quality, latency, cost,and long-term system health.Leverage modern infrastructure including PostgreSQL, Redis, Kubernetes,vector stores, and streaming technologies to power our Client's real-time AIworkflows.Engage in hands-on coding, model development, code reviews, andperformance optimizations, setting the standard for applied ML excellenceacross the team.Tech Lead Manager, AI 2Champion AI quality"”accuracy, calibration, robustness, latency, and theguardrails that make AI outputs trustworthy in an enterprise context.Implement best practices in evaluation, observability, drift detection, and A/Btesting to ensure reliability and measurable customer impact.People Management & Team Leadership (~30%)Manage, mentor, and grow a team of ML engineers and applied AI engineers,owning their career growth, performance reviews, and professionaldevelopment.Conduct regular 1:1s, provide timely and constructive feedback, and createindividual development plans for each report.Foster a culture of psychological safety, trust, accountability, and continuousimprovement.Own team planning: scope AI work with Product and Design, participate insprint planning and Agile ceremonies, and remove blockers.Drive hiring for the team"”defining roles, conducting interviews, and makinghiring decisions to build a world-class AI engineering team.Maintain team health by monitoring workload, preventing burnout, andensuring sustainable delivery.Cross-Functional CollaborationPartner with Product Managers and Designers to translate product vision intowell-defined AI problem statements and technical plans.Communicate progress, model performance, risks, and trade-offs clearly toengineering leadership and non-technical stakeholders.Collaborate across Engineering, Data, and Platform teams to drive alignmenton shared data, features, evaluation infrastructure, and serving systems.What We're Looking ForB.S. or M.S. in Computer Science, Machine Learning, or a related field, orequivalent experience.Tech Lead Manager, AI 37+ years of hands-on software engineering experience with a strong appliedML background"”shipping production ML systems, not just prototypes orresearch.2+ years of engineering management or tech lead experience, including directreports, mentorship, and team-level delivery ownership.Strong proficiency in Python and modern ML frameworks (PyTorch,TensorFlow, or equivalent), plus comfort in at least one backend language(Python, Node.js, or Ruby) for productionizing services.Deep understanding of the applied ML lifecycle: problem framing, datapipelines, feature engineering, training, evaluation, deployment, andmonitoring.Hands-on experience with LLMs and modern AI tooling"”prompt design,retrieval-augmented generation, fine-tuning, agentic workflows, andevaluation of non-deterministic systems.Proven experience designing, building, and operating scalable ML systems indata-heavy environments.Solid grasp of software engineering best practices: testing, code review,CI/CD, design documentation, reproducibility.Experience with RESTful APIs, relational databases (PostgreSQL), vectordatabases, and cloud-native architecture (Kubernetes, containerization,microservices).A systems-level thinker who balances model quality with pragmatic, business-aware decision-making around cost, latency, and time-to-ship.Excellent communication skills"”you can translate complex ML concepts forboth engineers and non-technical stakeholders, and set realistic expectationsabout what AI can and can't do.Demonstrated ability to balance technical execution with people leadership"”comfortable context-switching between shipping models and coachingengineers.Early-stage startup experience (Seed to Series C) preferred"”comfortablewearing multiple hats and building in fast-moving environments.Tech Lead Manager, AI 4Nice to HaveExperience building agentic systems, tool-using LLM pipelines, or multi-stepreasoning workflows in production.Familiarity with time-series forecasting, recommendation systems, orworkforce/operations modeling.Background in MLOps tooling (MLflow, Weights & Biases, Ray, Kubeflow) orlarge-scale data pipeline orchestration (Airflow, Dagster, Prefect).Experience with real-time analytics and streaming infrastructure such asRedis, Kafka, or Apache Pinot.Experience building and scaling AI teams in a high-growth startupenvironment.Knowledge of evaluation frameworks for LLM-based systems and experiencedesigning offline/online eval harnesses.Why Join Our Client?High Impact: Deploy technology that changes how enterprises plan, manage,and scale their workforce.Deep Technical Ownership: Work directly in code"”not just configuresystems"”and ship meaningful solutions to real customers.Cross-Functional Exposure: Operate at the intersection of Engineering,Product, and Design.Growth & Learning: Build expertise in enterprise-scale systems, datareliability, and AI-driven automation.Benefits: Competitive compensation, meaningful equity, world-classmedical/dental/vision coverage, and a flexible remote-first culture with teamevents, offsites, and happy hours.If you're passionate about building AI systems at scale, love developing people asmuch as models, and want to be part of a company growing at rocket speed, we'dlove to hear from you.

Created: 2026-05-12