Lead Platform Engineer – Agentic System

Our organization is developing an
Agentic AI Platform
designed to orchestrate intelligent, autonomous workflows that drive decision-making, automation, and innovation across diverse domains.

As the
Lead AI Platform Engineer
, you will be responsible for architecting and implementing the foundational elements of this platform. This includes designing, deploying and maintaining production grade
multi-agent systems with most effective frameworks
including
CrewAI, LangGraph
, or equivalent systems, and deploying these solutions at scale on modern cloud infrastructure. You will work on and collaborate closely with other data engineers, data scientists, ML engineers, and product teams to realize our vision of adaptive, reasoning-driven systems.

Key Responsibilities

• Architect & Build Agentic Systems:
  Design, develop, and deploy multi-agent workflows leveraging frameworks such as
  CrewAI, LangGraph
  , or custom-built orchestration layers.
• Platform Engineering:
  Construct the underlying
  agentic runtime
  , encompassing message routing, memory management, and context-sharing mechanisms between agents.
• LLM & Tool Integration:
  Integrate Large Language Models (e.g., OpenAI, Anthropic, or open-source alternatives), vector databases, retrieval systems, and external APIs for agent tool-use and reasoning capabilities.
• Workflow Design & Optimization:
  Collaborate with AI researchers and solution engineers to design dynamic agent workflows that adapt based on contextual information and analytical results.
• Cloud & Scalability:
  Architect scalable, cost-efficient deployments utilizing
  AWS, GCP, or Azure
  , leveraging cloud-native components (e.g., Lambda, ECS, Kubernetes, Pub/Sub) to ensure high availability and performance.
• Observability & Governance:
  Implement comprehensive monitoring, evaluation metrics, and safety checks for autonomous agents to ensure reliability and compliance.
• Team Leadership & Mentorship:
  Provide guidance to a team of engineers, establish best practices for agent development, and cultivate a high-performance engineering culture. Take sessions for the team and build tog-grade skills in the area across the company.

Required Qualifications

• Strong background in Python
  , with demonstrated experience in asynchronous programming, API development, and distributed systems.
• Proven experience in building
  LLM-powered multi-agent systems
  using
  CrewAI
  ,
  LangGraph
  ,
  LangChain
  , or similar orchestration frameworks.
• Deep understanding of
  prompt engineering
  ,
  RAG pipelines
  , and
  tool-calling mechanisms
  .
• Hands-on experience with
  cloud infrastructure
  (AWS/GCP/Azure) and
  MLOps
  components (e.g., Kubernetes, Docker, CI/CD, API Gateway).
• Solid understanding of
  state management
  ,
  context persistence
  , and
  memory architecture
  for agents.
• Experience integrating
  vector stores (e.g., FAISS, Pinecone, Chroma, Weaviate)
  and
  LLM APIs
  (e.g., OpenAI, Claude, Gemini).
• Demonstrated ability to
  architect scalable AI systems
  from prototype to production.
• Excellent communication and collaboration skills, with the ability to translate complex technical concepts into actionable platform features.
• Experience with
  Graph-based orchestration
  or
  LangGraph advanced workflows
  .
• Familiarity with
  CrewAI "crew and task" paradigms
  or other agent coordination frameworks.

Nice-to-Have

• Exposure to
  event-driven architectures
  ,
  message queues
  , or
  knowledge graphs
  .
• Understanding of
  AI safety, alignment
  , and
  governance principles
  .
• Contributions to open-source agent frameworks or AI orchestration tools.
• Ability to customize models to specific purposes.

What We Offer

• An unparalleled opportunity to
  build the next-generation Agentic AI Platform
  from inception.
• The chance to work with
  cutting-edge LLM orchestration technologies
  and
  cloud-native AI systems
  .
• Competitive compensation and potential equity options.
• A collaborative, innovation-driven culture with a strong focus on real-world impact