Engineering Manager - Applied ML & Platform
Leena AI
Software Engineering, Other Engineering, Data Science
Gurugram, Haryana, India
Posted on Jun 9, 2026
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 Overview
Leena 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 Responsibilities
Engineering Leadership
Experience & Background
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
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 Overview
Leena 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 Responsibilities
Engineering 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.
- 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.
- 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.
- 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.
- 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.
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).
- 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.
- 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.
- Excellent communication skills with both technical and non-technical stakeholders.
- Ability to explain ML concepts and risks clearly to product and business partners.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (Tier 1 preferred).
- 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.
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