AI Technical Lead

No Corps please Business Title: Technical Lead - AI Platform JOB SUMMARY: Our client is seeking a Technical Lead - AI Platform to architect, build, and lead full-lifecycle AI/ML product development—from data pipelines and model training to GenAI integration and intelligent app deployment. This is an end-to-end role for a builder-leader: someone who thrives on writing production code, deploying machine learning systems, integrating LLMs, and leading an elite team of engineers and ML practitioners. Key Responsibilities: • Architect & Build Full-Stack AI Solutions • Design and build end-to-end machine learning systems—including pipelines, feature stores, training/inference services, and monitoring. • Architect scalable, modular applications that embed foundation models, retrieval-augmented generation (RAG), and agentic workflows directly into product experiences—all on Google Cloud Platform (GCP) or Oracle Cloud Infrastructure (OCI). • Develop privacy-preserving ML systems that align with food industry compliance and traceability standards. • Build explainable AI frameworks to enable business stakeholders to trust and validate model outputs. • Design AI architectures that deliver tenant-aware intelligence while ensuring strict data isolation and performance SLAs across our multi-tenant SaaS platform. Hands-On Engineering • Develop robust data pipelines using BigQuery, Dataflow, and Apache Beam. • Train, tune, and deploy ML models using TensorFlow, PyTorch, and Scikit-learn. • Build full-stack AI-native applications with Python, Java, React/Angular, and GCP-native services. ● Implement robust MLOps pipelines that ensure reproducible training, CI/CD deployment, cost-efficient scaling, and real-time model monitoring. GenAI & AI Agent Development • Integrate GenAI features: RAG pipelines, content summarization, Q&A, semantic search synthetic data generation, and multi-turn chat interfaces • Design and develop AI agents and copilots using LangChain, CrewAI, and Vertex AI to automate complex business processes. • Use vector databases (FAISS, Pinecone) to build domain-specific LLM workflows. • Prototype and deploy multi-agent systems for autonomous decision-making and workflow execution across supply chain, pricing, traceability, and forecasting. Technical Leadership ● Lead a high-impact team of ML engineers and AI developers. ● Set technical strategy, define best practices, and guide architectural decision-making. ● Work cross-functionally with Product, Data Science, and Executive teams to shape AI innovation and delivery. What you’ll need: ● 10+ years in software/ML engineering; 5+ years leading architecture and engineering teams. ● Proven experience building production-ready AI/ML pipelines and applications end-to-end. ● Expertise in GenAI frameworks (OpenAI, Vertex AI), multi-agent architectures, and MLOps tooling. ● Experience operationalizing LLMs for enterprise use cases: hallucination reduction, security, cost optimization, and monitoring. ● Track record of shipping high-quality intelligent products quickly and at scale. ● Strong team leadership, communication, and cross-functional collaboration skills. Tech Stack: Languages & Frameworks: ● Python, Java, SQL, JavaScript/TypeScript ● TensorFlow, PyTorch, Scikit-learn ● React, Angular Cloud Platform: ● GCP – Vertex AI, BigQuery, Cloud Functions, Cloud Run, Dataflow, Pub/Sub ● OCI – Data Science, Autonomous Data Warehouse, Functions, Container Engine for Kubernetes (OKE), Data Flow, and Streaming Data & MLOps: ● BigQuery, AlloyDB, MongoDB, Redis ● MLflow, Kubeflow, Airflow ● Docker, Kubernetes, GitHub Actions, Terraform ● GenAI & Agents: ● Vertex AI Gemini, OpenAI, Claude ● LangChain, LlamaIndex, FAISS, Pinecone ● RAG pipelines, autonomous agents, multi-agent orchestration, memory modules, tool use, prompt chaining Dev Tools: ● GitHub Copilot, ChatGPT, Cursor AI, Locofy