Engineering Manager – AI Platforms at Sia Partners - United Kingdom

Mumbai, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

04 Aug, 26

Salary

0.0

Posted On

06 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

People Management, LLM Platforms, RAG Architectures, MLOps, GenAIOps, Kubernetes, Docker, Vector Databases, Cloud-Native AI Services, Agile/Scrum, Distributed System Design, NLP, Deep Learning, Model Validation, CI/CD, Responsible AI

Industry

Business Consulting and Services

Description

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 Sia Partners is looking for an Engineering Manager – AI Platforms 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. As an Engineering Manager, you will serve as the bridge between Data Science research and production-grade software engineering. You will be responsible for the health, growth, and delivery of a cross-functional team, ensuring that our data-driven AI services are scalable, secure, and seamlessly integrated into our global consulting framework. You will not only guide the technical architecture of our Large Language Model (LLM) platforms but also foster a culture of scientific excellence, rapid experimentation, and professional development. Your leadership will ensure that Sia remains at the forefront of the AI landscape, transforming complex statistical models and algorithms into robust, platform-centric solutions that deliver measurable value to our clients worldwide. Key Responsibilities Team Leadership & Mentoring: Manage, coach, and grow a team of Software Engineers, ML & GenAI Engineers. Conduct performance reviews, define career paths, and foster an inclusive environment that encourages innovation in algorithmic design and deployment. Platform Strategy: Own the roadmap for Sia’s AI Platforms, evolving them from experimental models to enterprise-grade foundations that support RAG, agentic workflows, and automated model fine-tuning at scale. Data Science Excellence: Oversee the development of scalable machine learning workflows, ensuring best practices in statistical rigor, model validation, and the transition from research notebooks to production-ready code. MLOps & GenAIOps Governance: Drive the adoption of robust MLOps pipelines (CI/CD, model monitoring, drift detection) to ensure the reliability and observability of deployed Data Science models. Cross-Functional Collaboration: Partner with Lead Data Scientists, Product Managers, and Cloud Architects to align technical execution with business objectives and client needs. Technical Oversight: Provide architectural guidance and conduct reviews for complex AI integrations involving vector databases, orchestrators (LangChain, LlamaIndex), and multi-cloud environments. Security & Compliance: Ensure all AI platforms adhere to global security standards (GDPR, SOC2) and implement Responsible AI guardrails to mitigate bias and ensure data privacy in model training and inference. Stakeholder Communication: Act as a technical advocate, translating complex Data Science and platform capabilities into clear, value-driven insights for executive leadership. Qualifications Experience: 8+ years of experience in the data/software space, with at least 3+ years in a formal people management or technical leadership role leading Data Science or ML teams. Data Science Mastery: Deep understanding of the Data Science lifecycle, including exploratory data analysis, feature engineering, and advanced modeling techniques (Deep Learning, NLP, etc.). AI/GenAI Depth: Hands-on experience building and scaling applications powered by LLMs (OpenAI, Claude, Llama) and implementing complex RAG architectures. Platform Expertise: Proven track record with Kubernetes, Docker, and cloud-native AI services (AWS Bedrock/SageMaker, Azure AI, or Google Vertex AI). Infrastructure: Solid understanding of vector databases (Milvus, Pinecone, Weaviate) and distributed system design for large-scale data processing. Management Skills: Strong experience in Agile/Scrum methodologies, capacity planning, and managing globally distributed teams. AI-Native Engineering Leadership: Experience managing teams that utilize Cursor, GitHub Copilot, or Claude Code as a core part of their daily workflow. Education: Bachelor’s or Master’s degree in Data Science, Computer Science, AI, or a related quantitative field. Soft Skills: Exceptional emotional intelligence, conflict resolution, and the ability to inspire a team during rapid technological shifts. EM - Product Traits (What Success Looks Like) Platform Ownership: Owns AI platform foundations (infra, tooling, pipelines) as long-lived products Enablement First: Measures success by how fast and safely product teams ship using the platform Technical Depth: Understands AI/ML platform trade-offs (compute, latency, cost, scalability, security) Production Readiness: Ensures platforms support model productionization, monitoring, and lifecycle management Reliability & Scale: Drives uptime, resilience, and performance for multi-team AI workloads Developer Experience: Reduces friction in CI/CD, environments, experimentation, and deployments Cost & Efficiency Awareness: Balances performance with cloud and compute cost controls Cross-Team Alignment: Works closely with Product EMs, Staff Engineers, and DevOps to align platform roadmaps Team Leadership: Builds and grows strong platform, DevOps, and ML-infra engineers Calm Ownership: Leads with clarity and accountability during incidents and scaling challenges 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.

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Responsibilities

Lead and grow a cross-functional team of engineers to design and deliver scalable, production-grade AI and Generative AI platforms. Bridge the gap between data science research and software engineering to implement RAG, agentic workflows, and MLOps governance.