Company Description
Founded in 2018, Leena AI is an autonomous conversational AI–backed employee experience platform built for large enterprises. Trusted by 10M+ employees across companies such as Nestlé, Puma, AirAsia, Coca-Cola, Abbott, Sony, and HDFC Bank, Leena AI has powered 30M+ conversations and 1B+ employee interactions globally.Leena AI integrates seamlessly with 100+ enterprise platforms including SAP SuccessFactors, ADP, Oracle, Workday, Microsoft 365, and Slack, and supports 100+ languages. The company has raised $40M from Greycroft and Bessemer Venture Partners.Role OverviewLeena AI is seeking an Engineering Manager with experience leading ML-driven teams to build scalable, production-grade AI systems. This role blends people leadership, system design, and applied machine learning ownership.You will lead a team of engineers working across backend services, ML systems, and AI-powered features, while partnering closely with Product, Data, and Research teams. The ideal candidate has prior hands-on experience as an ML IC, understands the realities of taking models to production, and can coach teams through both engineering and ML-specific challenges.Key ResponsibilitiesEngineering Leadership
- Lead, mentor, and grow a cross-functional team of backend and ML engineers.
- Create a high-trust, high-ownership culture focused on quality, learning, and delivery.
- Support career development, performance management, and technical growth of team members.
ML & System Ownership
- Own delivery of ML-powered product features, from experimentation to production rollout.
- Guide teams on model lifecycle management: data preparation, training, evaluation, deployment, monitoring, and iteration.
- Ensure ML systems are reliable, observable, scalable, and cost-efficient in production.
Architecture & Technical Direction
- Drive architecture for distributed backend systems that integrate ML inference and data pipelines.
- Partner with senior ICs to make trade-offs around latency, accuracy, cost, and system complexity.
- Review designs and code across Node.js services, ML pipelines, and infrastructure components.
Execution & Delivery
- Plan and execute multi-quarter roadmaps spanning product engineering and ML initiatives.
- Balance experimentation velocity with enterprise-grade reliability and compliance.
- Ensure predictable, high-quality releases through strong execution discipline.
Cross-Functional Collaboration
- Work closely with Product, Data, Applied AI, and Customer teams to align technical execution with business outcomes.
- Translate product requirements into feasible ML and engineering plans.
- Represent engineering in roadmap, prioritization, and stakeholder discussions.
Requirements
Experience & Background
- 7+ years of software engineering experience, with prior hands-on IC work in ML or applied AI systems.
- 2+ years of experience managing engineers, ideally including ML or data-focused teams.
- Experience building and operating production ML systems (not just experimentation or research).
Technical Expertise
- Strong foundation in distributed systems and backend engineering (Node.js, APIs, cloud infrastructure).
- Practical experience with machine learning concepts such as model training, evaluation, inference, and monitoring.
- Familiarity with ML tooling and workflows (e.g., data pipelines, feature stores, model versioning, A/B testing).
- Ability to reason about ML-specific trade-offs: accuracy vs latency, offline vs online metrics, retraining strategies.
Leadership & Decision-Making
- Proven ability to lead teams through ambiguity and technically complex problem spaces.
- Strong judgment in balancing product needs, engineering rigor, and ML constraints.
- Comfortable being hands-on when needed, while primarily operating as a multiplier for the team.
Communication & Collaboration
- Excellent communication skills with both technical and non-technical stakeholders.
- Ability to explain ML concepts and risks clearly to product and business partners.
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (Tier 1 preferred).
Nice to Have
- Experience with conversational AI, NLP, recommender systems, or LLM-based systems.
- Prior experience scaling ML systems in B2B SaaS or enterprise environments.
- Exposure to MLOps practices in regulated or high-availability systems.
Why This Role
This role sits at the intersection of people leadership, platform engineering, and applied AI. You’ll shape how ML is built, shipped, and scaled inside a fast-growing enterprise AI company—while growing leaders and systems that directly impact millions of users.Skills: llm,node.js,enterprise,rag,ml
