Engineering Manager - Product (Python)

Job description Sia Partners is looking for an Engineering Manager - Product to support the design and delivery of next-generation AI and Generative AI platforms within Sia’s AI Factory. This role is pivotal in bridging high-level product vision with robust, cloud-native engineering execution. You will work closely with product, data science, and platform teams to translate business and client

requirements into robust technical solutions. The role requires strong Python expertise, experience with distributed systems and microservices, and a pragmatic approach to delivering reliable, scalable systems in enterprise environments. In addition to technical delivery, you will contribute to architectural decisions, raise engineering standards, and support client-facing engagements through technical leadership and clear communication.

Key

Responsibilities Team Leadership: Hire, coach, and retain top-tier software and cloud engineers. Establish trust through architectural design sessions and code reviews, fostering a culture of ownership, high performance, and continuous innovation. Cloud & Product Strategy: Define and drive quarterly technical roadmaps that align software delivery with business priorities.

Lead the evolution of our cloud ecosystem, focusing on scalability, cost-optimization, and seamless AI integration within our SaaS products. Architecture & Cloud Design Reviews: Ensure the highest standards of scalability, security, and performance across all cloud-based services. Embed architectural guardrails and "Cloud-First" best practices, ensuring documentation and coding guidelines are followed.

Hands-On Technical Influence: Contribute targeted PRs (scaffolding, Infrastructure-as-Code, developer experience improvements) to maintain a pulse on the codebase without occupying the critical delivery path. " Optimize CI/CD pipelines and cloud deployment strategies to increase delivery velocity while maintaining system stability. Cross-Functional Collaboration: Partner closely with Product Managers, Research, and Ops to transform ambiguous product

requirements into actionable technical milestones, ensuring frequent delivery of customer-visible value. Talent Development: Engage in recruiting and empowering premier engineering talent. Attract and develop engineers who excel in collaborative environments and are passionate about building world-class software products.

Qualifications Education: Master’s or PhD in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or Physics. Over 8 years in software development, with at least 2 years in a leadership role managing software or cloud engineering teams. Proven track record in the technology product sector with a deep understanding of SaaS lifecycles. Core Skills: Expertise in algorithms, data structures, and distributed systems.

Deep understanding of cloud-native design patterns and microservices architecture. js is highly valued. AI-Native Engineering Leadership: Experience managing teams that utilize Cursor, GitHub Copilot, or Claude Code as a core part of their daily workflow. Cloud Expertise: Extensive experience building and launching modern SaaS products on public cloud platforms, specifically AWS.

Proficient in containerization and orchestration (Docker, Kubernetes) and Infrastructure-as-Code (Terraform/CloudFormation). Leadership & Communication: A decisive leader who prioritizes action and outcomes. Outstanding interpersonal skills with the ability to collaborate across global functions. Strong command of English (written and verbal) for effective communication at all organizational levels.

Global Collaboration: Demonstrated ability to lead in a global environment, attracting and retaining top engineering talent while working across different time zones and cultures. EM - Product Traits (What Success Looks Like) AI Product Ownership: Owns delivery of AI/GenAI products from problem framing to production impact. Outcome-Driven Delivery: Focuses on business value, not just model or feature completion.

Product–Engineering Alignment: Partners tightly with Product / Business to convert AI use cases into executable plans. Technical Judgment: Understands AI system trade-offs (latency, cost, accuracy, reliability) and challenges decisions when needed. Delivery Predictability: Breaks complex AI initiatives into incremental, shippable milestones. Quality & Reliability: Ensures production-grade AI systems (monitoring, failure handling, iteration readiness).

Client & Stakeholder Communication: Clearly explains AI limitations, risks, and trade-offs to non-technical stakeholders. Team Leadership: Builds and grows high-ownership product engineers and applied AI teams. Managing Ambiguity: Operates effectively with evolving

requirements and experimental problem spaces. Calm Ownership: Leads with accountability under delivery pressure and changing priorities. Additional information What We Offer Opportunity to lead cutting-edge AI projects in a global consulting environment. Leadership development programs and training sessions at our global centers. A dynamic and collaborative team environment with diverse projects. Position based in Mumbai (onsite) Sia is an equal opportunity employer.

All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.