Software Engineering Manager

Manage the full software project lifecycle from business requirements and planning through development, testing, deployment, production, and continuous improvement.

Translate Business Requirements into clear, scalable, secure, and executable technical solutions.

Lead and coordinate Backend, Frontend, Mobile, QA, DevOps, Database, and UI/UX teams as required.

Design, review, and approve Software Architecture and Solution Architecture for new and existing systems.

Review major technical decisions before implementation and ensure appropriate technical trade-offs are documented.

Ensure software quality, code maintainability, performance, security, availability, and scalability.

Define and manage technical roadmaps, release plans, priorities, backlogs, and delivery milestones.

Oversee Agile/Scrum execution, sprint commitments, dependencies, blockers, and delivery timelines.

Identify technical risks and bottlenecks early and define practical mitigation and recovery plans.

Lead troubleshooting of complex software and production incidents, including Root Cause Analysis and corrective actions.

Review APIs, integrations, third-party services, and interoperability between applications and systems.

Establish and enforce standards for coding, architecture, security, testing, deployment, and documentation.

Improve engineering practices, CI/CD, testing quality, release processes, observability, and deployment reliability.

Monitor and reduce technical debt while protecting delivery speed and product stability.

Ensure accurate and maintainable technical documentation for systems, integrations, environments, and operational procedures.

Evaluate new technologies, frameworks, tools, platforms, and vendors before adoption.

Manage outsourcing partners and third-party technology providers; review technical proposals, solution designs, quotations, and RFP responses.

Participate in interviewing, selecting, evaluating, mentoring, and developing technical team members.

Provide management with clear reports on project status, progress, risks, blockers, decisions required, and release readiness.

AI & INNOVATION RESPONSIBILITIES

• Identify practical opportunities to integrate AI into existing products, new products, and internal engineering workflows.
• Evaluate and implement Generative AI, Large Language Models (LLMs), AI Agents, RAG, NLP, Machine Learning, and intelligent automation where they create measurable value.
• Work with AI APIs and platforms such as OpenAI, Azure OpenAI, or equivalent technologies.
• Lead Proof of Concept initiatives and evaluate quality, cost, latency, security, privacy, and scalability before production adoption.
• Use AI-assisted engineering tools to improve requirements analysis, coding productivity, code review, testing, debugging, documentation, and data analysis.
• Define appropriate governance, security, and data privacy controls for AI-enabled solutions.

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• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related field.
• 8+ years of professional software development/engineering experience, including at least 3 years in a technical leadership or engineering management role.
• Strong prior hands-on software development background and proven ability to review technical designs and engineering decisions.
• Proven experience managing web, backend, mobile, and integrated software products or platforms.
• Strong understanding of Software Architecture, Solution Architecture, System Design, APIs, Databases, Cloud, Security, Integration, and Scalability.
• Experience managing multiple projects, products, or workstreams simultaneously.
• Strong understanding of Agile, Scrum, SDLC, release management, production operations, and incident resolution.
• Strong analytical, troubleshooting, prioritization, stakeholder management, and communication skills.
• Ability to communicate effectively with developers, management, vendors, and non-technical stakeholders.
• Good English communication and technical documentation skills.

PREFERRED QUALIFICATIONS

• Microservices Architecture, Cloud Architecture (Azure/AWS or similar), DevOps, CI/CD, Docker, or containerized environments.
• Enterprise Architecture / Solution Architecture experience; TOGAF or related architecture certification is an advantage.
• Experience with SaaS platforms, enterprise systems, high-availability applications, or complex third-party integrations.
• Practical experience with AI/ML, LLMs, Generative AI, RAG, AI Agents, or AI-enabled products.
• Experience with cybersecurity, secure software development, vendor management, and technical proposal evaluation.