Solutions Engineering Manager

Overview

The Solutions Engineering Manager leads the solution engineering practice as an internal product and service, covering people, standards, demand intake, reusable patterns, governance, and delivery quality across enterprise technology platforms. The practice spans Microsoft Azure, Amazon Web Services, integration, APIs, automation, containers, and web hosting.

What you'll do

• Define and maintain the solution engineering practice strategy, operating model, service definition, and multiyear roadmap.
• Manage the practice as an internal service with defined customers, engagement models, adoption targets, and success measures.
• Translate business and technology demand into a prioritised, resourced delivery plan.
• Establish the practice's position in the delivery lifecycle and its interfaces with architecture, platform teams, and operations.
• Maintain a transparent backlog and communicate priorities, capacity, and trade-offs to stakeholders.
• Own demand intake, including qualification, sizing, prioritisation, and acceptance criteria for engagements.
• Establish a clear front door for business functions seeking technical solutions, with predictable response and triage.
• Define and operate engagement models spanning advisory, assisted delivery, and full end-to-end solution delivery.
• Own solution design standards, design documentation templates, architecture decision records, and non-functional requirement baselines.
• Establish and run design review and technical assurance processes proportionate to solution risk and reach.
• Ensure solutions favour approved platform capabilities, golden paths, and reference architectures over bespoke build.
• Set the bar for technical quality and hold the team to it through review, feedback, and correction.
• Build and curate a library of reusable solution patterns, modules, reference implementations, and accelerators.
• Measure and drive reuse, actively reducing repeated bespoke solutions to the same problem.
• Identify recurring demand that should become a productised platform capability and make the case to the relevant platform team.
• Embed AI-assisted engineering into the team's working methods, with appropriate review and quality controls.
• Own the quality, timeliness, and cost of solutions delivered by the practice.
• Ensure every solution meets operational readiness criteria before production release, including monitoring, runbooks, and support arrangements.
• Track and reduce defects, rework, post-implementation incidents, and unplanned support burden.
• Embed security, compliance, and data-protection requirements into the practice's design and delivery standards.
• Partner with Cybersecurity, Architecture, Risk, Quality, and Compliance teams to maintain approved patterns.
• Ensure designs use approved identity, secrets, and certificate services, including Entra ID, HashiCorp Vault, and CyberArk.
• Track and manage technical debt, design exceptions, unsupported solutions, and remediation commitments.
• Manage practice budgets, forecasts, resourcing, and cost-optimisation initiatives.
• Evaluate the total cost of ownership of delivered solutions, including support and lifecycle effort, not just build cost.
• Manage delivery partners and contract resources, including performance measures and contractual commitments.
• Lead, coach, and develop a team of solution engineers spanning junior and experienced levels.
• Build team capability through workforce planning, clear accountabilities, structured development paths, and certification.
• Manage performance, career progression, and the progression of engineers between levels.
• Build relationships with business function leaders, platform managers, architecture, cybersecurity, and operations leaders.
• Facilitate decisions across teams with competing requirements and priorities.
• Communicate practice performance, risks, roadmap progress, and investment needs to senior leadership.
• Deliver solutions to agreed scope, quality, cost, and timeline.
• Increase reuse of approved patterns and platform capabilities.
• Reduce bespoke build relative to platform consumption.
• Reduce lead time from demand intake to delivered solution, defects, rework, post-implementation incidents, security findings, and audit exceptions.
• Improve supportability and reduce unplanned support burden of delivered solutions.
• Build stakeholder satisfaction, repeat demand from business functions, team capability, certification, and progression between levels.
• Convert recurring demand into productised platform capabilities.

What you'll need

• Significant experience in solution engineering, platform engineering, technical delivery, or solution architecture, typically ten or more years.
• At least four years leading teams.
• Experience leading technical delivery across multiple technology domains at enterprise scale.
• Strong technical breadth across cloud platforms, integration and APIs, automation, containers, and hosting.
• Experience establishing design standards, technical assurance, and delivery quality practices.
• Experience managing roadmaps, service portfolios, technical debt, and technology lifecycles.
• Experience integrating security, compliance, and governance controls into design and delivery workflows.
• Ability to lead distributed, cross-functional teams and influence senior stakeholders.
• Ability to develop engineers and grow technical capability within a team.
• Strong financial, vendor-management, communication, and organisational skills.

Nice to have

• Experience operating a solution engineering or technical consulting practice in a global, regulated enterprise.
• Hands-on background in cloud, integration, automation, or hosting engineering, retained credibly into leadership.
• Experience with GitHub, Terraform, Ansible, Kubernetes, OpenShift, Backstage, and modern delivery toolchains.
• Experience with observability platforms including Datadog, Dynatrace, Prometheus, Grafana, Splunk, Cribl, or Observe.
• Familiarity with platform-product management, internal developer platforms, and golden-path delivery models.
• Familiarity with AI-assisted engineering and its practical adoption within delivery teams.
• Experience working within a validated, GxP, or otherwise regulated environment, including data-protection obligations such as GDPR.
• Certifications such as AWS or Azure professional level, TOGAF or an architecture qualification, ITIL, or an agile or product-management qualification.
• A bachelor's degree in computer science, engineering, information technology, or a related discipline.

Details

• Location: Hyderabad.
• Lead a team of approximately five to ten solution engineers across junior and experienced levels.
• The practice spans Microsoft Azure, Amazon Web Services, integration, APIs, automation, containers, and web hosting.