Job Summary
We are looking for an experienced Engineering Manager to lead globally distributed engineering teams and manage a portfolio
of customer projects. The role combines engineering leadership, AI-enabled delivery, technical solutioning, customer
engagement, and project P&L ownership. The ideal candidate will have strong technical expertise, experience working with
global customers, and a proven record of delivering complex software programs while driving customer success, profitability,
and AI-led innovation.
Role focus: 60% leadership, delivery, customer engagement, and P&L management; 40% AI-enabled engineering, technical
leadership, solutioning, innovation, and pre-sales
Must-Have Skills & Experience
- 12-15 years of software engineering experience, including at least 5 years in an Engineering Manager or similar leadership
- role.
- Experience leading distributed engineering teams and managing multiple fixed-bid, T&M, support, maintenance, or
managed-service engagements.
- Strong customer-facing experience, including independently leading customer discussions, managing senior stakeholders,
and handling escalations.
- Experience working directly with customers in the US and/or Europe; prior onsite customer engagement or onsite
assignment is highly preferred.
- Strong technical background in modern application development, cloud, APIs, microservices, DevOps, CI/CD, and software
architecture.
- Experience in technical solutioning, estimation, architecture discussions, and pre-sales support.
- Proven ownership of project/account P&L, including revenue, gross margin, utilization, budgeting, forecasting, billing, and
profitability improvement.
- Practical experience driving AI-enabled engineering and delivery using AI tools to improve productivity, quality, automation,
and delivery outcomes.
- Strong knowledge of Agile, Scrum, SDLC, engineering governance, resource planning, risk management, and delivery
management.
Good-to-Have Skills
- Experience delivering AI solutions, PoCs, or enterprise AI initiatives using GenAI, RAG, AI Agents, or intelligent automation.
- Retail/eCommerce domain experience and experience working in a mid-sized software services organization.
- PMP, Scrum, AWS/Azure, or AI certifications; experience contributing to account growth and strategic customer initiatives
Key Responsibilities
- Lead, mentor, and grow engineering teams while building a culture of ownership, accountability, innovation, financial
- awareness, and continuous learning.
- Own end-to-end delivery across discovery, architecture, estimation, planning, development, testing, deployment, and
production support.
- Manage project scope, schedule, quality, risks, dependencies, resources, customer communication, and escalations across
multiple engagements.
- Build trusted customer relationships and translate business needs into practical, scalable, and commercially viable technical
or AI-enabled solutions.
- Drive AI-assisted engineering across requirements, design, coding, code review, testing, documentation, modernization,
debugging, estimation, and support.
- Identify customer AI opportunities and collaborate with architects, AI specialists, data teams, and product teams to shape
PoCs, pilots, and production solutions.
- Measure AI impact on productivity, quality, timelines, cost, utilization, margins, and customer outcomes while ensuring
security, privacy, responsible use, and human review.
- Own project/account P&L, including revenue, gross margin, utilization, delivery cost, forecasting, billing readiness, revenue
leakage, and recovery actions.
- Improve profitability through resource-mix optimization, pyramid management, utilization, scope control, delivery
predictability, automation, and AI-assisted productivity.
- Provide technical oversight for architecture, engineering standards, cloud adoption, DevOps, security, modernization,
performance, and maintainability.
- Support pre-sales through discovery, solutioning, estimation, proposals, pricing inputs, technical presentations, PoCs,
renewals, and account-growth initiatives.
- Ensure compliance with contractual commitments, delivery governance, security policies, audit requirements, timesheets,
billing processes, and organizational controls
Success Measures
- Projects delivered within agreed scope, quality, timelines, and budget.
- Achievement of revenue, utilization, gross-margin, and profitability targets with accurate forecasting and timely billing.
- Strong customer satisfaction, stakeholder confidence, team performance, retention, and capability development.
- Measurable improvement in engineering productivity, quality, predictability, automation, and AI adoption.
- AI opportunities identified, proposed, piloted, converted, or delivered, with contribution to solutioning, renewals, and account
growth.
