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