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Publicis Groupe

Runs advertising and digital transformation services

Senior Manager Software Engineering

Engineering LeadershipPosted on Nov 11
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree or equivalent experience in Computer Science, Engineering, Information Technology, or a related field, or equivalent practical experience.
  • At least 13 years of software engineering experience, including at least 5 years leading multiple engineering teams in customer-facing environments.
  • Demonstrated success delivering complex, enterprise-scale software programs and leading multi-functional teams using Agile delivery practices.
  • Experience managing engineering leaders and teams while balancing client commitments, technical strategy, delivery outcomes, quality, and people development.
  • Strong technical understanding of C#, .NET/.NET Core, REST APIs, microservices, distributed systems, object-oriented design, design patterns, and modern web architecture.
  • Working knowledge of React or Angular, JavaScript/TypeScript, HTML5, CSS, and responsive application design.
  • Strong understanding of SQL, PL/SQL, relational and NoSQL data modelling, database performance, data integration, batch and real-time processing, and enterprise data platforms.
  • Ability to guide architecture, engineering standards, application security, performance, observability, quality engineering, automated testing, troubleshooting, and production support.
  • Experience with Git-based collaboration, peer review, Agile engineering, structured release management, and enterprise change governance.
  • Ability to connect technology choices to business outcomes, customer experience, delivery risk, talent capability, and long-term maintainability.
  • Strong AI architecture capability across retrieval-augmented generation, agentic systems, model evaluation, guardrails, identity, data protection, observability, and cost/performance trade-offs.
  • Demonstrated architecture ownership for a meaningful AI solution from discovery through implementation, evaluation, and operational readiness.
  • Exposure to LangChain, LangGraph, CrewAI, Amazon Bedrock, Azure AI, or comparable AI frameworks and services.
  • Ability to define AI strategy, prioritize use cases, guide prototypes, assess feasibility and risk, establish adoption measures, and scale successful practices.
  • Ability to promote AI-assisted ways of working across analysis, architecture, development, testing, documentation, knowledge management, and support with appropriate controls.
  • Strong customer focus, business insight, critical thinking, and ownership.
  • Leadership, coaching, mentoring, communication, presentation, negotiation, and stakeholder-management capability.
  • Adaptability, resilience, decisiveness, and results orientation while remaining open to challenge and new evidence.
  • Professionalism, integrity, sound judgment, transparency, and accountability in decisions affecting customers, people, and technology.

Responsibilities

  • Lead engineering outcomes across multiple teams and initiatives, balancing business priorities, client commitments, technical strategy, quality, talent development, and innovation.
  • Own end-to-end delivery of multiple strategic software programs, ensuring predictable execution, measurable outcomes, quality, transparency, and timely management of risks and dependencies.
  • Lead planning, estimation, engineering, testing, implementation, transition, and production stabilization across build, enhancement, modernization, migration, and maintenance initiatives.
  • Align capacity, skills, priorities, milestones, and dependencies across teams; make informed trade-offs and identify material risks with clear mitigation options.
  • Establish outcome-focused governance using delivery health, quality, productivity, customer impact, and operational measures.
  • Ensure alignment to engineering standards, security, privacy, compliance, accessibility, documentation, and support-readiness expectations.
  • Promote continuous improvement through retrospectives, root-cause analysis, reusable practices, automation, and evidence-based decision-making.
  • Partner with clients, product leaders, business collaborators, architects, analysts, quality leaders, data teams, and operations teams to understand objectives and shape scalable solutions.
  • Lead customer workshops, solution discussions, technical presentations, roadmap conversations, and executive governance forums.
  • Build trusted relationships, establish clear expectations, manage issues constructively, and communicate decisions, trade-offs, risks, and mitigation plans transparently.
  • Translate business objectives into technology strategies, investment priorities, capability roadmaps, and measurable engineering outcomes.
  • Communicate delivery health, key performance indicators, solution risks, quality trends, innovation progress, and strategic recommendations to senior partners.
  • Architect model and framework strategy, retrieval-augmented generation and knowledge architecture, embeddings and vector search, prompt/context management, tool integration, agent orchestration, memory, guardrails, evaluation, and human oversight.
  • Define and implement an AI adoption roadmap across engineering, analysis, quality, support, knowledge management, and customer-solution use cases.
  • Identify high-value generative AI and agentic AI opportunities, prioritize use cases, sponsor prototypes, define success measures, and scale proven patterns responsibly.
  • Promote effective use of frameworks and services such as LangChain, LangGraph, Amazon Bedrock, Azure AI, Amazon Q, Kiro, Microsoft Copilot, or equivalent technologies.
  • Apply responsible AI practices covering privacy, security, intellectual property, data handling, model limitations, accuracy, bias awareness, explainability, traceability, and accountable human oversight.
  • Create an environment that supports responsible experimentation, reusable accelerators, knowledge sharing, and measurable improvement in engineering productivity and customer value.
  • Provide architectural direction and technical guidance across enterprise web, API, integration, distributed, data, and AI-enabled solutions.
  • Guide conversion of high-level designs into detailed designs covering components, APIs, data models, algorithms, schemas, integration contracts, security, resilience, performance, and non-functional requirements.
  • Partner with architects and technical leads to evaluate solution options and ensure scalability, security, maintainability, observability, accessibility, and cost effectiveness.
  • Drive engineering excellence through design reviews, code reviews, architecture governance, quality standards, technical-debt management, performance analysis, and root-cause prevention.
  • Maintain sufficient hands-on technical awareness to challenge assumptions, assess feasibility, guide complex decisions, and support resolution of critical engineering issues.
  • Promote modern engineering patterns for C#/.NET, Python, JavaScript/TypeScript, React or Angular, APIs, event-driven systems, distributed applications, and data-intensive workloads.
  • Own the quality strategy across teams, including testability, automation, code quality, data quality, performance, resilience, security validation, and production readiness.
  • Ensure quality is built into discovery, design, development, and support rather than treated as a separate downstream activity.
  • Establish review mechanisms, test coverage expectations, traceability, defect-prevention practices, release validations, and operational acceptance criteria.
  • Use trends from defects, incidents, customer feedback, and engineering measures to direct corrective and preventive improvements.
  • Promote AI-assisted test design, review, defect analysis, and knowledge discovery while requiring accountable validation of generated outputs.
  • Guide scalable data modelling, integration, batch and real-time processing, data-quality controls, and performance strategies across enterprise solutions.
  • Provide oversight for solutions using Oracle, MySQL, DynamoDB, Redshift, Snowflake, or equivalent data platforms.
  • Guide designs involving REST APIs, event-driven patterns, microservices, integration platforms, and technologies such as SnapLogic, DataHub, or equivalents.
  • Ensure data solutions address reliability, lineage, security, privacy, interoperability, and business usability.
  • Lead, coach, and mentor engineering managers, technical leads, and engineers across multiple teams.
  • Build a high-performance culture grounded in accountability, inclusion, collaboration, engineering excellence, continuous learning, and customer focus.
  • Drive workforce planning, hiring, onboarding, goal alignment, regular feedback, career development, succession planning, recognition, retention, and employee engagement.
  • Develop future-ready capabilities across software engineering, architecture, quality, data, AI, automation, client engagement, and domain knowledge.
  • Create clear ownership and decision mechanisms while empowering leaders and teams to implement effectively.
  • Address performance and team-health concerns fairly, consistently, transparently, and in alignment with organizational policies.
  • Enable teams to flex across business analysis, architecture, development, quality engineering, data, automation, documentation, and production support based on delivery priorities while preserving role depth and accountability.
  • Use workflow automation and low-code tools such as n8n, Make, Zapier, or equivalent technologies to streamline repeatable engineering and business processes where appropriate.
  • Encourage cross-skilling, communities of practice, reusable assets, structured knowledge management, and movement across adjacent responsibilities.
  • Continuously improve engineering practices, operating models, collaboration, customer responsiveness, and delivery efficiency using measurable evidence.

Desired Qualifications

  • Experience leading engineering for CRM, loyalty, marketing technology, customer data, high-volume transaction, or large-scale distributed platforms.
  • Experience with data and integration technologies such as Redshift, Snowflake, DynamoDB, SnapLogic, DataHub, or equivalent platforms.
  • Experience using Python, scripting, workflow automation, n8n, low-code/no-code platforms, or equivalent technologies.
  • Experience establishing engineering communities, reusable accelerators, knowledge-management practices, or enterprise modernization programs.
  • Experience evaluating emerging technologies and translating successful experiments into governed, repeatable delivery capabilities.

About the Company

Publicis Groupe

Runs advertising and digital transformation services

Publicis Groupe runs advertising, media buying and digital transformation services for companies that want to reach consumers, coordinate campaigns and improve their business systems. Its agency network includes creative and media specialists, while Publicis Sapient builds and modernizes the technology behind clients' operations. Epsilon adds customer data and marketing technology that connect brands with audiences and measure campaign results. Clients pay for consulting, campaign creation and execution, with production and media costs billed through alongside the group's service work. Founded in 1926, Publicis Groupe is headquartered in Paris, France.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1926

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