2 months ago
Bengaluru, IndiaStaff+
Responsibilities
- Architect staged AI solution roadmaps and end-to-end solutions for client business problems across GenAI, agentic AI, multimodal, and applied ML use cases.
- Own reference architectures and design patterns for planning, tool use, memory, grounding, retrieval, and inter-agent communication.
- Lead multi-agent, multimodal, SLM, hybrid retrieval, knowledge graph, and enterprise deployment architecture.
- Establish evaluation frameworks, golden datasets, regression suites, guardrails, red-teaming, observability, reliability, and incident-response standards.
- Drive cloud, on-premises, and edge deployment practices including GPU operations, model serving, monitoring, and lifecycle automation.
- Shape the AI practice roadmap, mentor AI engineers, conduct technical reviews, and set hiring and engineering evaluation standards.
- Partner with engineering, data science, product, DX, clients, and business stakeholders on delivery, feasibility, risk, pre-sales, and solution estimation.
Requirements
- 10–12 years of hands-on experience building and deploying ML, deep learning, and AI systems in production, with progression into solution architecture and technical leadership.
- At least 10 years of experience delivering work for global businesses and large accounts.
- At least 3 years of hands-on GenAI and/or agentic AI experience beyond prompt engineering and basic RAG, including multi-agent systems, custom fine-tuning, multimodal pipelines, or SLM deployments.
- At least 3 years leading ML-AI technical pods or teams, mentoring senior engineers, and setting hiring and review standards.
- Advanced Python and SQL skills, plus strong backend engineering experience with FastAPI, Flask, or Django.
- Deep experience with LLMs, SLMs, RAG, agentic systems, multimodal architectures, knowledge graphs, fine-tuning, distillation, and quantization.
- Experience with evaluation frameworks, automated and human evaluation, red-teaming, guardrails, hallucination control, and AI observability.
- Strong foundations in predictive modeling, classical ML, deep learning, computer vision, NLP, time series, embeddings, and vector search.
- Deep experience with AWS, Azure, or GCP, model serving, GPU or accelerator operations, CI/CD, monitoring, and on-premises or edge deployment.
- Experience with Kafka, Spark or Flink, Hadoop, MongoDB, and NoSQL, graph, or vector stores; Salesforce and Adobe experience is a plus.
- Strong mathematical foundations in linear algebra, probability, statistics, and optimization.
- Excellent communication skills and the ability to explain technical trade-offs to engineers, business stakeholders, and clients.
- Willingness to work in a hybrid structure with at least three days per week in the office.
Benefits
- Full-time permanent position.
- Hybrid work arrangement requiring no less than three days per week from the office.
- Location: Bengaluru, India, Manyata N1 Block.
Tech Stack
Apache FlinkApache HadoopApache KafkaApache SparkAWSAzureDjangoFastAPIFlaskGoogle Cloud PlatformMongoDBPython
Categories
About Dentsu
Dentsu is a global advertising and marketing services group that plans and buys media, develops creative campaigns, and builds data- and technology-led customer experiences for brands. It earns revenue from agency fees and media services across a network that includes Carat, iProspect, and Merkle. Founded in 1901 and headquartered in Tokyo, Dentsu is publicly traded in Japan and serves clients across many sectors worldwide.