Engineering Manager
Software Engineering, Other Engineering
Gurugram, Haryana, India
Posted on Jul 17, 2026
About Leena AI
Leena AI is a leader in Agentic AI for the enterprise. We are building an iconic company, delivering AI Colleagues that transform back-office functions and accelerate the full promise of Generative AI - unlocking real productivity gains, cutting costs, and delighting employees at scale.
Leena AI provides the most forward-looking, open, and scalable Agentic AI architecture for the enterprise - it empowers CIOs and CTOs to develop, deploy, and manage AI Colleagues for the back office at scale. Built with full governance, compliance, security, and auditability at its core.
Leena AI integrates with 1000+ applications, including SAP, Salesforce, ServiceNow, Workday, and Microsoft Office 365. We are proud to be trusted by 500+ global enterprises and 20 million+ employees, including leading brands such as Nestlé, Puma, Coca-Cola, Sony, and Etihad Airways.
Founded in 2018 and headquartered in New York, Leena AI has secured over $40M in financing from top-tier investors including Greycroft, Bessemer Venture Partners, B Capital, and Y Combinator.
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 ResponsibilitiesEngineering Leadership
Leena AI is a leader in Agentic AI for the enterprise. We are building an iconic company, delivering AI Colleagues that transform back-office functions and accelerate the full promise of Generative AI - unlocking real productivity gains, cutting costs, and delighting employees at scale.
Leena AI provides the most forward-looking, open, and scalable Agentic AI architecture for the enterprise - it empowers CIOs and CTOs to develop, deploy, and manage AI Colleagues for the back office at scale. Built with full governance, compliance, security, and auditability at its core.
Leena AI integrates with 1000+ applications, including SAP, Salesforce, ServiceNow, Workday, and Microsoft Office 365. We are proud to be trusted by 500+ global enterprises and 20 million+ employees, including leading brands such as Nestlé, Puma, Coca-Cola, Sony, and Etihad Airways.
Founded in 2018 and headquartered in New York, Leena AI has secured over $40M in financing from top-tier investors including Greycroft, Bessemer Venture Partners, B Capital, and Y Combinator.
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 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.
- 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.
- 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.