We are seeking a highly skilled senior technical lead to join our Agentic AI and Semantic Search team. This is a hands-on technical leadership role responsible for designing scalable AI systems that integrate agentic reasoning with semantic search to deliver real-time, context-rich, and commerce-aware decisions.You will define the technical vision, lead architectural strategy, and build retrieval, reasoning, and evaluation platforms that directly impact how the world's top brands manage billions of dollars in eCommerce revenue.
Responsibilities
- Architecture and Leadership: Define and drive the architecture for agentic AI systems that combine LLM reasoning, semantic search, and contextual grounding.
- AI Agent Development: Design frameworks that allow agents to autonomously analyze data, retrieve context, and execute workflows across e-commerce platforms.
- Semantic Search Excellence: Build scalable retrieval systems leveraging vector databases, embeddings pipelines, hybrid search (dense + sparse), and re-ranking models.
- Agent-Oriented Design: Enable agents to access structured and unstructured commerce data (retailer catalogs, customer demand, supply chain signals) with contextual reasoning and memory.
- Metrics and Instrumentation: Define robust metrics for search relevance, grounding accuracy, reasoning quality, and business impact.
- Scalable Infrastructure: Architect distributed, low-latency, production-grade AI systems that serve mission-critical to CommerceIQ use cases.
- Cross-team Collaboration: Partner with Agentic AI engineers and product managers to turn AI innovations into scalable solutions.
- Mentorship and Influence: Provide technical guidance, mentor engineers, and champion best practices in system design and AI engineering.
AI Flywheel And Continuous Improvement
- Design and operationalize evaluation datasets and benchmarking frameworks for agents and semantic search.
- Integrate annotation and labeling workflows to generate high-quality training and evaluation datasets.
- Build feedback loops where customer signals and agent outcomes drive system improvements.
Requirements
- 6-12+ years of software engineering experience, including 3+ years in Senior IC roles.
- In-depth knowledge of LLMs, agent frameworks, orchestration (LangChain, LlamaIndex, CrewAI, etc. ), and retrieval-based methods.
- Experience in semantic search, retrieval systems, and distributed system design.
- Strong expertise in vector DBs (FAISS, Pinecone, Weaviate, Milvus), hybrid search, embeddings, and re-ranking models.
- Proven track record with RAG pipelines and integrating retrieval into LLM reasoning.
- Familiarity with evaluation dataset design, annotation tools (Labelbox, Scale AI, Prodigy, or in-house), and developing continuous evaluation pipelines.
- Proficient in Python and at least one systems language (Go, Java, or C++).
- Strong background in system design with the ability to lead end-to-end technical initiatives.
Nice-to-Have
- Experience with LLM fine-tuning, alignment, or reinforcement learning with human feedback (RLHF).
- Background in NLP/IR research, query understanding, or contextual search optimization.
- Experience with eCommerce / retail datasets and domain-specific semantic search challenges.
This job was posted by Vikas Sawant from CommerceIQ.
