Engineering Lead (AI & Automation Products)

Posted One Month Ago
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2 Locations
In-Office
Entry level
AdTech • Marketing Tech
The Role
Leads software engineering teams delivering AI and automation products. Owns technical architecture, PostgreSQL schemas, Claude integrations, document processing, workflow orchestration, DSP APIs, secrets management, multi-tenant access control, observability, cost attribution, and AI evaluation frameworks. Builds full-stack applications with Python APIs and React, establishes engineering standards, mentors developers, manages delivery accountability, and drives reusable platform components across products.
Summary Generated by Built In
The purpose of this role is to lead, develop and improve teams of software engineers with various skills, so that a high-quality end product is delivered. To provide technical guidance, to support analysis and design in order to deliver products aligned to the customer’s requirements and company standards.

Job Description:

Job Description
Technical Architecture & Delivery
  • Lead architecture decisions across the portfolio — schema design, API contracts, integration patterns, workflow orchestration, and when to integrate via direct API versus MCP (Model Context Protocol), weighing latency, control, security, auditability, and reusability tradeoffs

  • Hold delivery accountability — scope, timeline, quality — across all active workstreams, in partnership with the Director who owns product requirements and prioritization

  • Design and own the Postgres data schema underpinning the product (multi-table: pipeline data, access control, cost attribution, audit) — correctness and extensibility here is foundational, not incidental

  • Build and own the Claude/API integration layer: system prompt design and testing, multimodal document ingestion for XLSX, DOCX, PPTX, and PDF via reliable extraction/conversion pipelines, structured output parsing, schema validation, and fallback handling

  • Design practical automation workflows — background jobs, queues, retries, idempotency, human review points, run state, and replayable audit history for multi-step AI-assisted processes

  • Build and own third-party DSP API integrations (e.g. DV360, TTD) — OAuth flows, structured data file formats, read/write scoping by phase

  • Design and own secrets and credential management — API keys, OAuth credentials, Azure Key Vault or equivalent secrets manager; nothing in code or environment variables in source control

  • Design and own multi-tenant access control — role-based permissions, client-scoped data visibility, self-service onboarding

  • Design cost and usage attribution patterns — external API calls tagged and logged at the client and run level, feeding finance and program-level reporting as the portfolio scales

  • Review technical output against product requirements — flag when implementation doesn't match the requirement or the architecture is wrong for the problem

Team Leadership
  • Manage a team of junior and mid-level developers based in India — hiring input, onboarding, performance, growth planning

  • Run code reviews, pairing, and technical mentoring as a standing practice, not an occasional one

  • Set and enforce engineering standards: testing discipline, data validation, AI evaluation discipline, observability, and code quality bar

  • Standardize how the team uses Claude Code — establish shared conventions, prompt/context patterns, and reusable practices so the whole team improves its delivery quality, not just you

  • Run sprint-level technical planning and unblock the team day to day; escalate cross-team blockers to the Director rather than letting them stall delivery

Build Execution
  • Build full-stack applications end to end where needed: Python APIs (FastAPI or similar) and React/Tailwind front ends

  • Use Claude Code as a daily driver — both for personal output and as the standard tool your team is held to

  • Write tests, build data validation frameworks, and instrument observability across the pipeline, including prompt/model traces, structured-output validation, latency, cost, and failure analytics

  • Build and maintain practical evaluation harnesses for AI behavior — golden test sets, prompt/model versioning, regression checks, failure taxonomies, and release gates for higher-risk automations

  • Contribute to reusable component libraries and shared platform services that scale across clients and future portfolio products

Location:

Bengaluru

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent

Skills Required

  • Experience leading, mentoring, and developing software engineering teams
  • Experience making technical architecture decisions involving schemas, APIs, integrations, and workflow orchestration
  • Proficiency with Python API development using FastAPI or similar frameworks
  • Proficiency with React and Tailwind for front-end development
  • Experience designing and managing PostgreSQL data schemas
  • Experience integrating Claude or other AI APIs, including prompt design, structured outputs, validation, and fallbacks
  • Experience building multimodal document ingestion pipelines for XLSX, DOCX, PPTX, and PDF files
  • Experience designing background jobs, queues, retries, idempotency, human review, and audit histories
  • Experience integrating third-party APIs, OAuth flows, and secrets managers such as Azure Key Vault
  • Experience implementing multi-tenant, role-based access control and client-scoped data visibility
  • Experience writing tests, data validation frameworks, observability instrumentation, and AI evaluation harnesses
  • Experience using Claude Code as a daily development tool and standardizing team usage

dentsu Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about dentsu and has not been reviewed or approved by dentsu.

  • Parental & Family Support — Paid parental leave at full pay and caregiver supports (including backup care) are emphasized as standout elements. Feedback suggests family-oriented benefits are a strong part of the package.
  • Leave & Time Off Breadth — Flexible or unlimited PTO, extensive paid holidays, and a year-end office closure are established components. Feedback suggests time-off policies are generous and add meaningful flexibility.
  • Retirement Support — A large, established 401(k) plan with employer matching is clearly documented. Feedback suggests retirement benefits feel competitive and straightforward.

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The Company
HQ: Minato
15,492 Employees

What We Do

We are dentsu. We team together to help brands predict and plan for disruptive future opportunities and create new paths to growth in the sustainable economy. We know people better than anyone else and we use those insights to connect brand, content, commerce and experience, underpinned by modern creativity. We are the network designed for what’s next

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