Engineering Manager

Key Responsibilities

Technical Strategy & Architecture

Define and evolve the technical vision and architecture for the core AI foundation model platform.

Provide hands-on technical leadership and participate in high-level design.

Ensure scalability, reliability, and reusability of system components.

Drive best practices for coding standards, reviews, CI/CD, and technical debt management.

Team Leadership & Development

Build, mentor, and manage high-performing ML, backend, and frontend engineering teams.

Conduct 1:1s, performance reviews, and career development planning.

Promote a collaborative, inclusive, and learning-oriented engineering culture.

Project & Operational Management

Own full-cycle delivery: planning, resource allocation, timelines, and stakeholder alignment.

Collaborate closely with Product, UX/UI, and cross-functional teams to translate requirements into execution.

Implement and optimize Agile/Scrum processes, KPIs, and retrospectives.

Identify risks and implement mitigation strategies.

Engineering Rigor & Quality

Lead hiring efforts: define role profiles, interviewing, and selection processes.

Enforce strong quality practices including automated testing, monitoring, and incident management.

Oversee support operations, bug triage, and root-cause analysis.

Innovation & Continuous Improvement

Encourage design thinking, experimentation, and user-centric problem solving.

Evaluate and adopt new tools, architectures, and technologies.

Balance innovation with platform stability and compliance.

Stay updated with industry trends and ensure team capability enhancement.

Stakeholder & Client Engagement

Serve as the key technical liaison for internal stakeholders and external clients.

Present architecture proposals, roadmaps, and post-mortem analyses to leadership.

Integrate client feedback into product and engineering priorities.

Required Qualifications

12+ years of software engineering experience, including 5+ years in engineering management.

Strong expertise in modern tech stacks (Python, Java, C++, etc.) and cloud platforms (AWS, GCP, Azure).

Hands-on experience with microservices, Docker, Kubernetes, and scalable system architecture.

Experience managing production-grade platforms with high reliability.

Exposure to AI/ML systems, foundation models, or MLOps pipelines (highly preferred).

Proven ability to hire, grow, and retain top engineering talent.

Strong leadership in Agile methodologies, resource planning, and risk management.

Excellent communication skills; ability to present to executives and non-technical stakeholders.

Familiarity with trading systems, real-time data processing, or quantitative analytics (preferred).

Background in BFSI, financial services, or related domains is advantageous.

Bachelor’s/Master’s in Computer Science, Engineering, or equivalent field.