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Dentsu

Marketing analytics and digital advertising solutions

Engineering Lead - AI & Automation Products

Engineering LeadershipUpdated on Nov 13
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • 12–16 years of professional software engineering experience with deep Python expertise.
  • Demonstrated experience leading or managing a team of engineers, including code review, mentoring, and growth planning, not just individual contribution.
  • Strong experience designing and building production APIs in Python using FastAPI, Flask, or similar, and full-stack applications with React and Tailwind CSS.
  • Strong relational database experience, including schema design, normalization, and query performance; Postgres is preferred.
  • Strong practical proficiency with Claude Code or similar AI-assisted development tools, including agentic coding patterns and context management, and the ability to establish team standards for effective use.
  • Experience integrating LLM APIs such as Claude, OpenAI, or equivalent into production systems, including system prompt design, structured output parsing, and multimodal input handling.
  • Practical experience with tool-use/function-calling patterns, including defining tool schemas, validating arguments, handling tool results, chaining tool calls, and managing basic failure and retry behavior.
  • Strong context engineering fundamentals, including context window management, token budgeting, long-document handling strategies, and retrieval/context-selection patterns.
  • Awareness of prompt injection, adversarial inputs, and untrusted-document risks in AI systems, and ability to design guardrails for external briefs, trafficking sheets, platform exports, and other model-readable inputs.
  • Experience integrating third-party platform APIs with OAuth; general competency is sufficient and platform-specific experience is not required.
  • Working knowledge of secrets management and credential security practices in production systems, ideally including Azure Key Vault or equivalent managed secrets tooling.
  • Solid grasp of QA practices, data quality engineering, and AI evaluation, including unit and integration testing, data validation, golden datasets, regression evaluations, structured-output checks, and observability.
  • Practical understanding of human-in-the-loop AI systems, including adjudication workflows, labeled examples, accuracy measurement by parameter/category, feedback loops, and quality gates.
  • Experience with cloud infrastructure, preferably Azure, and modern deployment patterns including containers, CI/CD, managed identities, object storage, and background job/workflow execution.
  • Experience implementing background-processing or workflow patterns, including queues, scheduled jobs, retries, idempotency, status tracking, and operational monitoring.
  • Strong written and verbal communication for collaboration across distributed onshore (US) and offshore (India) teams.

Desired Qualifications

  • Exposure to LLM application and workflow frameworks beyond raw API calls, such as LangChain, LangGraph, CrewAI, Temporal, Azure Durable Functions, Celery/RQ, or equivalent agent/workflow tooling, useful as the portfolio expands into durable, multi-step automation in later phases.
  • Exposure to model selection and cost optimization strategies, including prompt caching, batching, tiered model selection by task complexity, latency/cost tradeoff analysis, and usage forecasting.
  • Background in media, advertising, or marketing technology data environments.
  • Exposure to data governance tooling such as Unity Catalog, attribute-based access control, or tag-driven policies.
  • Exposure to MCP servers or MCP-based developer workflows, with interest in when MCP is preferable to direct APIs for reusable tools, resources, prompts, and agent context.
  • Exposure to data flywheel concepts, including labeled corpora, adjudication data models, feedback capture, quality dashboards, and mechanisms that improve future AI behavior and inform phase-gate decisions.
  • Exposure to DV360 SDF (Structured Data Files), TTD API, or comparable adtech platform data formats/APIs.
  • Open-source contributions or public projects demonstrating full-stack or AI engineering work.

About the Company

Dentsu

Marketing analytics and digital advertising solutions

Dentsu International is a global marketing and advertising partner that helps brands grow by navigating the digital economy and using data-driven insights. Its services include consumer intelligence to understand customer behavior, digital marketing and advertising to reach audiences, customer experience management (CXM) to improve interactions, and gaming solutions to engage audiences. The company earns revenue through service fees, project work, and long-term contracts with a diverse mix of clients across retail, technology, and entertainment. Its approach combines research and analysis to set industry-focused insights and drive growth, while collaborating across disciplines to deliver integrated marketing solutions. Dentsu also pursues social impact initiatives, promoting inclusion and positive change in the industry and communities.

Company size
10,001+
Company stage
IPO
Headquarters
Tokyo, Japan
Founded
1901

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