AI Lead Architect at Merkle | AdTechTalent
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Merkle
AI Lead Architect
AI Deep Learning GenAI Agentic AI Multimodal SLM Python SQL FastAPI Flask Django Kafka Spark Flink Hadoop MongoDB NoSQL Graph databases Vector search AWS Azure GCP Transformers Machine Learning Prompt engineering Knowledge graphs Fine-tuning Multi-agent systems Software engineering Cloud
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Join Merkle and work on a role built for experienced AdTech operators.
Full job description Seeking AI Tech Lead to engineer, scale, govern, and grow AI delivery practice across GenAI, Agentic AI, and applied ML in enterprise engagements. Hands-on individual contributor and technical leader role requiring deep expertise in Deep Learning architectures, agentic AI, and software engineering. Responsibilities include leading end-to-end AI solution engineering, applying fail-fast logic to project management, performing trade-off analyses, owning reference architectures, designing multimodal agentic systems, establishing evaluation frameworks and safety standards, ensuring production readiness, mentoring engineers, enforcing AI in SDLC, engaging with clients and stakeholders, and supporting pre-sales. Requirements: 8+ years software development experience, 3+ years deep hands-on AI system deployment, expertise in GenAI/Agentic AI beyond basic API use, strong Python and SQL skills, backend engineering experience, cloud platform knowledge (AWS, Azure, GCP), and strong math foundations.
What you'll do Lead hands-on engineering for end-to-end AI solutions across Deep Learning, GenAI, Agentic AI, and multimodal use cases Similar jobs
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Bengaluru, India
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Apply 'fail fast' logic to AI project management to identify and disqualify unviable AI use cases early
Perform trade-off analysis on model class, retrieval design, memory optimization, and orchestration
Lead solutioning and architecture support for AI solutions including GenAI, Agentic AI, multimodal, and applied ML
Own reference architectures and solution design patterns for multimodal agentic systems
Conduct solution design reviews across client engagements and facilitate technical decisions
Design and lead build of multi-agent systems with reasoning, planning, tool use, persistent memory, and grounded retrieval
Lead multimodal system design across text, vision, speech, and structured data
Establish patterns for SLM design and adoption to meet enterprise constraints
Define hybrid retrieval and knowledge architectures spanning vector, graph, and NoSQL stores
Establish evaluation frameworks, golden datasets, regression suites, and observability for agentic and generative systems
Define and enforce safety, guardrail, and hallucination-control standards; lead red-teaming and adversarial testing
Set production readiness standards for reliability, latency, cost, monitoring, drift detection, and incident response
Lead GPU/accelerator operations, model serving, and lifecycle automation for deployments
Mentor engineers through code and architecture reviews to build permanent capability
Establish and enforce AI in SDLC frameworks on delivery projects
Engage with client and stakeholder leadership on architecture, feasibility, and risk
Support pre-sales and solutioning for new GenAI and Agentic AI opportunities including effort estimation and architectural framing Requirements Minimum 8+ years of total hands-on software development and engineering experience 3+ years of deep, hands-on experience building and deploying Deep Learning and AI systems in production Demonstrable hands-on work in GenAI and/or Agentic AI beyond basic API wrappers and simple RAG Experience with multi-agent systems, custom fine-tuning, or SLM-based deployment Deep practical grounding in neural networks, Transformers, predictive modeling, embeddings, vector search Experience with CV, NLP, and time series data Strong programming skills in Python and SQL Strong API and backend engineering experience with FastAPI, Flask, or Django Experience with cloud platforms such as AWS, Azure, or GCP Experience with Kafka, Spark/Flink, Hadoop, MongoDB, and other NoSQL/graph/vector stores Math foundations in linear algebra, probability, statistics, and optimization Tech stack Deep Learning GenAI Agentic AI Multimodal AI SLM Python SQL FastAPI Flask Django Kafka Spark Flink Hadoop MongoDB NoSQL Graph databases Vector stores AWS Azure GCP Transformers Predictive modeling Embeddings Vector search Computer Vision NLP Time series LLMs RAG Prompt engineering Knowledge graphs Fine-tuning (SFT, LoRA/QLoRA, RLHF/RLAIF) Distillation Quantization LangGraph LlamaIndex AutoGen
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Company
Merkle Merkle, a dentsu company, powers the experience economy. For more than 35 years, the company has put people at the heart of its approach to digital business transformation. As the only integrated experience consultancy in the world with a heritage in data science and business performance, Merkle delivers holistic, end-to-end experiences that drive growth, engagement, and loyalty. Merkle’s expertise has earned recognition as a “Leader” by top industry analyst firms, in categories such as digital transformation and commerce, experience design, engineering and technology integration, digital marketing, data science, CRM and loyalty, and customer data management. With more than 16,000 employees, Merkle operates in 30+ countries throughout the Americas, EMEA, and APAC.
Industry
Business Consulting and Services
Website
https://www.merkle.com
Posted
4 months ago
Category: Engineering
Chicago, United States; Detroit, United States; New York, US; Toronto, Canada • 5 months ago
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