Job Openings Lead AI Engineer

About the job Lead AI Engineer

Lead AI Engineer

Location: Remote (Global)

Team: AI & Systems Architecture

Summary

We’re looking for a Lead AI Engineer who combines strong leadership, hands-on engineering, and architectural expertise to design and deliver enterprise-grade AI solutions. You’ll lead teams building intelligent systems from AI agents and chatbots to automation platforms and data pipelines while working directly with clients to define strategy, guide architecture, and ensure successful implementation.

You should be equally comfortable discussing high-level system design with executives as you are diving into backend APIs, frontend logic, or mobile integrations.

Requirements (Must-Haves)

  • Excellent English communication skills you’ll interact directly with clients, lead technical discussions, and translate complex solutions into clear business outcomes.

  • 6+ years of professional software engineering experience, with at least 3 years leading cross-functional or distributed engineering teams or technical delivery units.

  • Proven experience as a Solution Architect having built and deployed multiple production applications across Backend, Frontend, and Mobile platforms.

  • Strong Full-Stack experience in modern stacks such as Node.js, GoLang, or Python for backend systems, React for frontend and React Native, Swift and Kotlin for mobile.

  • Proven experience designing and deploying AI-powered systems (agents, multi-agent collaboration, chatbots, classification engines, automation pipelines) in production environments at scale.

    • Experience designing and maintaining data ingestion and transformation pipelines using Python frameworks (e.g., Airflow, Prefect, or custom ETL stacks) and AWS data pipelines (Glue, Step Functions, Lambda, S3, Redshift, etc.).

    • Hands-on experience building AI Agents or Chatbots using LangChain, LangGraph, Haystack, or equivalent orchestration frameworks

    • Proven experience with Retrieval-Augmented Generation (RAG) pipelines and vector databases such as pgVector, Pinecone, Weaviate, Chroma, etc.

    • Expertise in embedding generation, fine-tuning, and model evaluation pipelines.

    • Familiarity with the Model Context Protocol (MCP) for multi-agent communication.

    • Understanding of AI observability and evaluation frameworks (LangSmith, Traceloop, Helicone) and experience using them in production environments.

  • Strong understanding of cloud-native environments (AWS, GCP, or Azure) and modern CI/CD best practices.

  • Deep understanding of system design, scalability, and distributed architectures.

  • Strong product intuition able to bridge the gap between technical feasibility and business value.

Requirements (Nice-to-Haves)

  • Experience with A2A (Agent-to-Agent) communication systems and coordination strategies.

  • Experience with Voice Agents, Vision Analysis, or multimodal AI systems.

  • Deep understanding of data governance, model lifecycle management, and AI compliance frameworks (PII, access control, red-teaming).

Bonus Points

  • Expertise in AI-driven automation (Zapier, AutoGen, CrewAI, or similar ecosystems).

  • Experience mentoring other engineers in AI architecture and solution delivery.

  • Experience working in Startup-like environments

  • Experience with Evolving Architectures system Design

  • Experience with 4-dimensional Software Arquitecture framework

Reporting

You’ll report directly to the CTO, overseeing technical direction for AI projects while collaborating with product, data, and engineering teams. You’ll act as the primary technical interface for clients, ensuring architectural excellence, delivery quality, and alignment with strategic goals.