1 hour 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
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About Dentsu
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.