Company Description
Sia Partners is a next-generation global management consulting firm, founded in 1999 and headquartered in Paris, France. The firm is recognised for its innovative approach, combining strategy and management consulting with data science and creativity. Sia Partners serves a diverse range of sectors, including energy, banking, healthcare, and technology, providing services to over 1,000 clients worldwide, including many Fortune 500 companies. With a strong emphasis on delivering tangible results and superior value, Sia Partners is committed to helping clients navigate the digital revolution and achieve transformation. The firm operates with a global presence, employing over 3,500 consultants across 48 locations in 20 countries
Our Mumbai office was launched in 2024, marking an exciting new chapter for us. We’re building the team with people who are eager to shape something from the ground up — combining the agility and entrepreneurial energy of a startup with the backing and reach of a global brand.
Job Description
We are seeking a Staff Engineer to support the design and delivery of next-generation AI and Generative AI platforms within Sia’s AI Factory. This is a hands-on engineering role focused on building scalable, production-grade systems where LLMs, agentic workflows, and machine learning models integrate seamlessly with cloud-native backend services.
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
Define and own architecture for backend systems (primarily Python) that integrate AI/ML into production services.
Deploy, optimize, and scale ML models in collaboration with Data Science and Data Engineering.
Design and maintain cloud infrastructure using Terraform and Helm; support deployments on GCP/AWS.
Lead containerization and orchestration best practices (Docker, Kubernetes) for development and production.
Ensure data integrity and performance across SQL and NoSQL systems (Postgres, MongoDB, etc.).
Establish and maintain monitoring and observability: Prometheus, Grafana, logging (Loki/ELK) and alerting.
Ship backend microservices and platform tooling: APIs, auth, data pipelines, batch/streaming components.
Contribute to product architecture decisions for both SaaS products and client implementations.
Act as a technical contact on client-facing projects—translate requirements into technical designs and guide delivery.
Qualifications
Education: Master’s or PhD in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or Physics.
8+ years engineering experience (or equivalent) building backend systems, demonstrable ownership of architecture and delivery.
Strong Programming in python, java or JavaScript expertise, experience building microservices and backend tooling.
Hands-on experience with containerization (Docker) and orchestration (Kubernetes).
Practical experience with Terraform, Helm, and cloud platforms (GCP/AWS).
AI-Native Engineering: Experience utilize Cursor, GitHub Copilot, or Claude Code as a core part of their daily workflow.
Familiarity with deploying/operating ML models in production; comfortable collaborating with Data Science.
Solid knowledge of relational and NoSQL databases and performance tuning.
Experience with monitoring/observability stacks (Prometheus, Grafana, ELK/Loki).
Proven track record mentoring engineers, leading cross-team initiatives, and influencing technical strategy.
Excellent communicator, able to translate technical trade-offs to engineering leadership and Stake holders.
Comfortable owning triage, incident decisions, and conducting RCAs.
Staff Engineer Traits (What Success Looks Like)
Thinks in systems, not just features.
Acts as a force multiplier for technical teams.
Drives clarity in ambiguous technical situations.
Chooses long-term maintainability over short-term hacks.
Communicates complex ideas with precision and calm authority.
Leads through technical credibility, not hierarchy.
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.
