This is a hiring opportunity for Nobroker , The Lead AI Engineer is a senior, hands-on technical leader responsible for architecting and building the production systems that power our generative AI platform. You will be our senior expert on engineering and deploying complex, scalable AI systems, with a special focus on agentic AI and MLOps for LLMs.

Lead the design, development, and scaling of our core AI agent architecture, including

multi-agent orchestration, tool integration, and state management.

● Architect and build high-throughput, low-latency RAG (Retrieval-Augmented Generation)

pipelines, optimizing for cost, speed, and accuracy.Design and implement robust MLOps infrastructure for the entire LLM lifecycle (e.g., model

serving, evaluation, monitoring, and continuous deployment of fine-tuned models).

● Build and maintain the core infrastructure for deploying and managing LLM-powered

applications in a secure, scalable, and cost-effective way.

● Implement comprehensive monitoring, logging, and observability for our AI systems to track

performance, detect drift, and ensure reliability.

● Own the CI/CD pipelines for AI components, ensuring rapid and safe iteration.

● Lead the development of our core agent-building frameworks and libraries, making them more

powerful, efficient, and easier for our customers to use.

● Collaborate with the Data Science team to productionize their research, turning new models and

algorithms (e.g., novel RAG techniques, fine-tuned models) into scalable platform features.

● Partner closely with the Product team to translate platform requirements into concrete

engineering designs and roadmaps.

● Act as a key technical partner to our Forward Deployed Engineering team, providing them with

the robust tools and platform they need to succeed with customers.

● Mentor junior engineers on the team, establishing best practices for software engineering,

system design, and MLOps.

Qualifiecations

MS in Computer Science, Software Engineering, or a related field.

7+ years of hands-on software engineering experience, with at least 4+ years focused on building

and deploying production-grade Machine Learning or AI systems.

● Demonstrable, hands-on experience in engineering production systems using the modern Gen AI

stack. You must have:

● Proven experience building and scaling RAG pipelines.

● Deep expertise with agentic frameworks (e.g., LangChain, LlamaIndex) and a strong

understanding of how to build custom, production-ready agentic systems from the ground up.

● Experience with MLOps for LLMs, including model serving, monitoring, and evaluation.

● Expert-level proficiency in Python.

● Strong experience with cloud platforms (AWS, GCP, or Azure), containerization (Docker,

Kubernetes), and CI/CD systems.

● Experience building and scaling data-intensive, real-time applications.

Deep experience with vector databases (e.g., Pinecone, Weaviate, Milvus).

● Experience with data processing and pipeline tools (e.g., Kafka, Spark, Airflow).

● Strong understanding of REST APIs, gRPC, and microservices architecture.

● You are a systems-level thinker who can manage complexity, work with ambiguity, and build for

scale.