Senior Technical Lead- Machine learning

At , we're building the Retail Co-Pilot - AI Commerce Platform of the future. Our mission is to help the world's leading consumer brands win in digital commerce by combining AI-driven insights, autonomous decision-making, and intelligent execution across retail channels like Amazon, Walmart, Instacart, and more.

The Agentic AI & Semantic Search team sits at the heart of this mission. We are building intelligent AI agents that can reason, plan, and act, powered by semantic search, retrieval, and contextual understanding. Our systems drive the AI flywheel, where data, models, evaluation, and feedback continuously improve to deliver business-critical outcomes for our customers.

We are seeking a highly skilled Senior Technical Lead o join our Agentic AI & 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.

• Architecture & 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.
  
  
• AI Flywheel & 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.
    
    
• Metrics & 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 & Influence: Provide technical guidance, mentor engineers, and champion best practices in system design and AI engineering.

• 8-10 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.

• 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.

• Commerce-First AI: Passion for applying AI to solve real-world commerce problems.
• Builder Mindset: Thrives in ambiguity and can translate vision into scalable systems.
• Pragmatic Innovation: Balances cutting-edge research with enterprise-grade reliability.
• Leadership Without Authority: Influences across teams through technical depth and clarity.