Be at the Forefront of the Agentic AI Revolution

At Skan AI, we are pioneering the context engine for human and agentic execution, bringing context from enterprise operators, systems, and processes to power how the world's largest organizations execute their most complex, mission-critical work.

Why Skan AI

We're in hyper-growth mode at exactly the right moment in history. As enterprises race to adopt agentic AI, we're uniquely positioned to deliver the clear signal they desperately need: a platform that trains and grounds AI Agents in trillions of real execution signals, enabling reliable, compliant automation of their most complex processes.

Backed by Dell Technologies Capital and other leading investors, we're the only company that can bridge the gap between AI's promise and enterprise reality, making us perfectly positioned to define the agentic era for modern enterprises.

Our diverse, collaborative team of 250+ innovators is solving category-defining challenges at the intersection of AI, process intelligence, and enterprise work. Diverse perspectives fuel breakthrough thinking, cross-functional collaboration is the norm, and our work directly transforms how Fortune 500 companies operate. We are shaping the future of work itself.

About the Role

We're looking for a hands-on Senior Engineering Manager to own the delivery, health, and growth of one of our engineering teams. You are accountable for what the team ships, how predictably, and how well its people grow. You are a strong engineer yourself — hands-on in code, design, and architecture, and making technical calls alongside your Lead, Staff Engineer, and Architects.

You partner closely with product, Data Science, and other teams to set direction and deliver together. The team builds cloud-native, microservices-based services at the heart of our agentic-AI, LLM-powered product — so you're managing delivery where AI moves from experimentation into dependable production. Your success is a team that ships the right things, on time, at high quality, and grows while doing it.

What You'll Own

- Delivery: a team that ships the right things, predictably, at a high quality bar.
- People: engineers who grow, perform, and want to stay.
- Engineering practice: the standards, tooling, and feedback loops — spanning AI-native engineering — that keep quality and delivery visible.
- Technical direction: credible, hands-on technical leadership alongside your Lead, Staff Engineer, and Architects.
- Data Pipeline production: Data Science work delivered into dependable, product-ready outcomes.

Responsibilities Delivery, Planning & Execution





Goal: the team ships the right things, predictably, at a high quality bar.

- Own delivery outcomes — turn priorities into a transparent roadmap and realistic commitments you're accountable for.
- Drive planning rigor — estimation, sprint and release planning, tracking, forecasting, and dependency, risk, and scope management.
- Stay technical and hands-on — review code and designs, shape architecture, and make technical calls with your Lead, Staff Engineer, and Architects.

People & Team Building Goal: engineers who grow, perform, and want to stay.

- Grow the people — 1:1s, feedback, growth plans, and performance managed directly.
- Build the team — attract, assess, and onboard strong engineers for now and for scale.
- Own health and culture — a motivated, inclusive team, with burnout and attrition risk watched closely.

Process & Operational Health Goal: a healthy operating rhythm, with engineering standards and feedback loops you build and sustain.

- Run the operating rhythm — own Agile ceremonies and ways of working; keep them lightweight and effective.
- Build and own ai-native engineering best practices — establish the standards (code review, testing, CI/CD, definition of done, quality gates, and effective engineering) and put in place the tooling and feedback loops that give the team visibility into quality and delivery, not just uphold what already exists.
- Improve with metrics — use velocity, quality, DORA-style signals, and team feedback to remove friction.

Cross-Functional & Stakeholder Management Goal: aligned stakeholders and Data Science work that reaches production.

- Align with product and peers — priorities, dependencies, and expectations across teams.
- Partner closely with Data Science — own delivery of DS work into dependable, product-ready outcomes, aligned with product and technical direction.
- Communicate up and out — honest status, early risk-flagging, and clear representation of the team to leadership.

Qualifications

Required

- Experience: 12+ years in software engineering, incl. 5+ years managing engineers, delivering complex software and growing people.
- Delivery ownership:



proven end-to-end ownership of a team's roadmap and commitments — estimation, sprint/release planning, tracking, forecasting, risk and scope, predictable delivery.
- People leadership: hiring, growing, and retaining engineers — 1:1s, feedback, growth plans, performance handled directly.
- Technical strength (must-have): strong, hands-on background — ideally cloud-native microservices — deep enough to review code and designs, engage in architecture, and make sound technical calls. A technical management role, not purely people-management.
- Engineering best practices: track record of building and instilling engineering practice — code review, testing, CI/CD, definition of done, quality gates.
- Process & agile: fluent in Agile/Scrum and modern delivery; runs a healthy operating rhythm and improves it with metrics.
- Cross-functional & communication: excellent communication and stakeholder management; partners with product and represents the team to leadership.

Preferred

- Experience managing teams that build AI/ML- or LLM-powered products, or that work closely with data science teams.
- Experience growing a team through a high-growth or scaling phase.
- Familiarity with our stack (Python, Kubernetes, microservices, PostgreSQL/MongoDB, Azure) or close equivalents.
- Bachelor's or Master's in Computer Science, Information Technology, or a related field — or equivalent experience.

Why Skan AI?

- Own a team end to end — its delivery, its health, and the growth of its people — with real accountability and real support.
- Lead engineers building the services that put agentic AI into production for the world's largest enterprises.
- Lead as a technical manager — stay hands-on in architecture and code while you grow a team and own its delivery, alongside a strong Lead, Staff Engineer, and Architects.
- Shape and grow a team in a high-growth, category-defining company, alongside talented engineers, data scientists, and product leaders.

Skan AI is an equal opportunity employer committed to building a diverse, inclusive, and respectful workplace around the world. We do not discriminate based on race, color, religion or belief, sex (including pregnancy, sexual orientation, gender identity, or gender expression), national origin, ancestry, age, disability, medical condition, genetic information, marital or family status, military or veteran status, or any other characteristic protected by applicable laws in the locations where we operate. We welcome people from all backgrounds and provide reasonable accommodations throughout the hiring process.

📌 Senior Engineering Manager (Bengaluru)
🏢 Skan.ai
📍 Bengaluru