Engineering Manager

About us slice the way you bankslice’s purpose is to make the world better at using money and time, with a major focus on building the best consumer experience for your money. We’ve all felt how slow, confusing, and complicated banking can be. So, we’re reimagining it. We’re building every product from scratch to be fast, transparent, and feel good, because we believe that the best products transcend demographics, like how great music touches most of us.Our cornerstone products and services: slice savings account, slice UPI credit card, slice UPI, slice UPI ATMs, slice fixed deposits, slice borrow, and UPI-powered bank branch are designed to be simple, rewarding, and completely in your control. At slice, you’ll get to build things you’d use yourself and shape the future of banking in India. We tailor our working experience with the belief that the present moment is the only real thing in life. And we have harmony in the present the most when we feel happy and successful together.We’re backed by some of the world’s leading investors, including Tiger Global, Insight Partners, Advent International, Blume Ventures, and Gunosy Capital.About the roleWe’re looking for Engineering Manager to lead our Data Platform and MLOps teams at slice. In this role, you’ll be responsible for building and scaling a high-performing team that powers data infrastructure, real-time streaming, ML enablement, and data accessibility across the company. You'll partner closely with ML, product, platform, and analytics stakeholders to build robust systems that deliver high-quality, reliable data at scale. You will drive AI initiatives to centrally build AP platform and apps which can be leveraged by various functions like legal, CX, product in a secured manner.This is a hands-on leadership role perfect for someone who enjoys solving deep technical problems while growing people and teams.What You Will DoLead and grow the data platform pod focused on all aspects of data (batch + real-time processing, ML platform, AI tooling, Business reporting, Data products – enabling product experience through data)Maintain hands-on technical leadership - lead by example through code reviews, architecture decisions, and direct technical contributionPartner closely with product and business stakeholders to identify data-driven opportunities and translate business requirements into scalable data solutionsOwn the technical roadmap for our data platform including infra modernization, performance, scalability, and cost efficiencyDrive the development of internal data products like self-serve data access, centralized query layers, and feature storesBuild and scale ML infrastructure with MLOps best practices including automated pipelines, model monitoring, and real-time inference systemsLead AI platform development for hosting LLMs, building secure AI applications, and enabling self-service AI capabilities across the organizationImplement enterprise AI governance including model security, access controls, and compliance frameworks for internal AI applicationsCollaborate with engineering leaders across backend, ML, and security to align on long-term data architectureEstablish and enforce best practices around data governance, access controls, and data qualityEnsure regulatory compliance with GDPR, PCI-DSS, SOX through automated compliance monitoring and secure data pipelinesImplement real-time data processing for fraud detection and risk management with end-to-end encryption and audit trailsCoach engineers and team leads through regular 1:1s, feedback, and performance conversationsWhat You Will Need 9+ years of engineering experience, including 2+ years managing data or infra teams with proven hands-on technical leadershipStrong stakeholder management skills with experience translating business requirements into data solutions and identifying product enhancement opportunitiesStrong technical background in data platforms, cloud infrastructure (preferably AWS), and distributed systemsExperience with tools like Apache Spark, Flink, EMR, Airflow, Trino/Presto, Kafka, and Kubeflow/Ray plus modern stack: dbt, Databricks, Snowflake, TerraformHands on experience building AI/ML platforms including MLOps tools and experience with LLM hosting, model serving, and secure AI application developmentProven experience improving performance, cost, and observability in large-scale data systemsExpert-level cloud platform knowledge with container orchestration (Kubernetes, Docker) and Infrastructure-as-CodeExperience with real-time streaming architectures (Kafka, Redpanda, Kinesis)Understanding of AI/ML frameworks (TensorFlow, PyTorch), LLM hosting platforms, and secure AI application development patternsComfort working in fast-paced, product-led environments with ability to balance innovation and regulatory constraintsBonus: Experience with data security and compliance (PII/PCI handling), LLM infrastructure, and fintech regulationsLife at sliceLife so good, you’d think we’re kidding:Competitive salaries. Period.An extensive medical insurance that looks out for our employees & their dependents. We’ll love you and take care of you, our promise.Flexible working hours. Just don’t call us at 3AM, we like our sleep schedule.Tailored vacation & leave policies so that you enjoy every important moment in your life.A reward system that celebrates hard work and milestones throughout the year. Expect a gift coming your way anytime you kill it here.Learning and upskilling opportunities. Seriously, not kidding.Good food, games, and a cool office to make you feel like home. An environment so good, you’ll forget the term “colleagues can’t be your friends”.