Engineering Lead (AI & Automation Products)

Merkle technologies s.r.o.

DGS India - Bengaluru - Manyata N1 Block Until 10/9/2026 12+ years exp H-1B sponsor history First posted July 7, 2026 Last posted August 10, 2026
Job description

Job Description:

Location: Location: DGS – India (overlap hours with US Eastern Time required)

Required Qualifications

  • 12–16 years of professional software engineering experience with deep Python expertise
  • Demonstrated experience leading or managing a team of engineers — code review, mentoring, growth planning — not just individual contribution
  • Strong experience designing and building production APIs in Python (FastAPI, Flask, or similar) and full-stack applications including React + Tailwind CSS front ends
  • Strong relational database experience — schema design, normalization, query performance — Postgres 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 (Claude, OpenAI, or equivalent) into production systems — system prompt design, structured output parsing, multimodal input handling
  • Practical experience with tool-use/function-calling patterns — defining tool schemas, validating arguments, handling tool results, chaining tool calls, and managing basic failure/retry behavior
  • Strong context engineering fundamentals — 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; ability to design guardrails for external briefs, trafficking sheets, platform exports, and other model-readable inputs
  • Experience integrating third-party platform APIs with OAuth (any domain) — general competency, not platform-specific
  • 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: unit and integration testing, data validation, golden datasets, regression evals, structured-output checks, and observability
  • Practical understanding of human-in-the-loop AI systems — adjudication workflows, labeled examples, accuracy measurement by parameter/category, feedback loops, and quality gates
  • Experience with cloud infrastructure (Azure preferred) and modern deployment patterns: containers, CI/CD, managed identities, object storage, and background job/workflow execution
  • Experience implementing background-processing or workflow patterns — 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

Preferred Qualifications

  • Exposure to LLM application and workflow frameworks beyond raw API calls: 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 — 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 — 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

Location:

DGS India - Bengaluru - Manyata N1 Block

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent
About this role

Summary

Lead AI and automation product engineering, managing teams, designing APIs, and integrating AI tools.

Job title

Engineering Lead (AI & Automation Products)

Experience level

12-16 years

Minimum experience

12+ years exp

Industry

marketing

Location requirements

Bengaluru, India; overlapping US Eastern Time, on-site preferred

Salary

Not specified

Visa sponsorship

H-1B sponsor history

Management role

Yes

Skills & keywords

Required skills

pythonapi designfull-stackdatabaseai toolssecurityqacloud

Preferred skills

langchainworkflow frameworksmodel optimizationdata governanceopen-source

Specializations

pythonapi designfull-stackai integrationcontext engineering
Locations

Structured locations inferred from the posting.

Bengaluru, Karnataka, India

On-site City