Engineering Manager

Netsmartz; Gurugram District; On-site; INR 2,800,000 - 4,800,000; Full time

Job summary

Netsmartz is seeking an Engineering Manager with delivery leadership to own client engagements end-to-end, from discovery to customer acceptance. The role blends technical consulting, solution ownership, and product management with AI-enabled delivery across the full lifecycle.

The ideal candidate combines a hands-on engineering background with delivery leadership, cloud/architecture knowledge, and strong client-facing communication to drive measurable business value for enterprise engagements.

Qualifications

• 9+ years in software engineering, technical consulting, solution delivery, or enterprise app development.
• Minimum 4 years leading enterprise software engagements.
• Proven experience owning client engagements across the complete SDLC.
• Strong knowledge of software architecture, APIs/integrations, microservices, cloud platforms (Azure), databases, and security fundamentals.
• Demonstrated ability to own a product backlog with epics, user stories, and acceptance criteria.

Responsibilities

• Lead client discovery workshops; analyze existing systems and workflows.
• Own the product backlog across the engagement lifecycle; define epics, features, and user stories.
• Own planning, sprint/release cadence, timelines, and scope; manage RAID and escalations.
• Own quality of BRDs, FRDs, Solution Design Docs, RTM, UAT docs, release notes, and SOW inputs.
• Participate in architecture reviews; flag technical risks early; ensure non-functional requirements are captured.
• Act as trusted advisor; run executive steering meetings; manage expectations; ensure measurable business value.
• Use AI to accelerate discovery, generate documentation and reporting, and identify automation opportunities.

Skills

Solution ownership

Client delivery

SDLC mastery

Agile leadership

AI tooling

Executive communication

Architecture knowledge

Backlog management

Pre-sales support

Education

Bachelor’s/Master’s in CS/Engineering

Tools

Jira

Azure

Confluence

Job description

Primary Expertise:

Solution Engineering, Client Delivery, Product & Project Leadership, Enterprise Software

Role Summary

The Engineering Manager owns client engagements end-to-end — turning business objectives into successful engineering outcomes. This role blends technical consulting, solution ownership, project leadership, and product management across the full lifecycle: discovery, planning, execution, release, and customer acceptance.

Unlike a traditional Engineering Manager, Product Owner, or Project Manager, this role sits at the intersection of business, architecture, engineering, and delivery — partnering closely with Solution Architects, Technical Leads, and Delivery Excellence. The ideal candidate has grown from a hands-on engineering background into delivery leadership: comfortable in architecture discussions, driving execution, and leading client conversations, without owning day-to-day development.

Core areas of ownership:

solution definition and backlog governance, project and delivery management, documentation governance, technical collaboration, and client relationship management — with AI embedded throughout.

Must Haves

• 9+ years in software engineering, technical consulting, solution delivery, or enterprise application development.
• Minimum 4 years leading enterprise software engagements.
• Proven experience owning client engagements across the complete SDLC.
• Strong working knowledge of software architecture, APIs/integrations, microservices, cloud platforms (Azure), databases, and security fundamentals — enough to engage credibly with architects and engineers without coding daily.
• Demonstrated ability to own a product backlog — writing epics, user stories, and acceptance criteria, and prioritizing based on customer value and delivery constraints.
• Experience running agile delivery (sprint planning, reviews, retrospectives, release planning) and project governance (RAID, milestones, scope, escalations).
• Practical, hands-on experience using AI tools (e.g., Copilot, ChatGPT, Claude, Gemini, Jira AI) for documentation, backlog management, reporting, or discovery — not just familiarity.
• Strong client-facing communication skills, including discovery workshops, executive updates, and stakeholder management.
• Bachelor's/Master's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.

Good to Haves

• Background as a Software Engineer, Senior Engineer, or Technical Lead before transitioning into delivery leadership.
• Certifications: Agile, Scrum, PMP, SAFe, Azure, AWS, or Business Analysis.
• Experience supporting enterprise pre-sales, RFPs, SOW creation, and digital transformation initiatives.
• Exposure to creating reusable solution accelerators or standardized discovery frameworks.
• Familiarity with AI-driven dashboards for project visibility and reporting.

Key Responsibilities

Client Discovery & Solution Consulting

• Lead discovery workshops; analyze existing systems and workflows.
• Define solution vision, roadmap, and implementation strategy.
• Support proposals, demos, and pre-sales technical-functional consulting.

Solution & Product Ownership

• Own the product backlog across the engagement lifecycle.
• Define epics, features, user stories, acceptance criteria, and business rules.
• Validate technical feasibility with architects; protect solution integrity through delivery.

Project & Delivery Management

• Own planning, sprint/release cadence, timelines, and scope.
• Manage RAID, dependencies, change requests, and escalations.
• Drive delivery tracking through to production readiness and customer sign-off.

Documentation & Governance

• Own quality and completeness of BRDs, FRDs, Solution Design Docs, RTM, UAT docs, release notes, and SOW inputs.

Technical Collaboration

• Participate in architecture reviews; flag technical risks early.
• Ensure non-functional requirements are captured before development starts.
• Facilitate trade-off discussions between business priorities and technical complexity.

Client Success

• Act as trusted advisor; build long-term stakeholder relationships.
• Run executive steering meetings; manage expectations proactively.
• Ensure delivered solutions realize measurable business value.

AI-Assisted Delivery

• Use AI to accelerate discovery, generate documentation/user stories, support backlog refinement, and produce reporting and executive summaries.
• Identify AI/automation opportunities within client processes and promote responsible AI adoption.