Lead Software Engineer

What you'll do

• Design and develop AI-native applications powered by LLMs and agent frameworks
• Architect end-to-end AI pipelines including ingestion, embedding, retrieval, reasoning, and response generation
• Define scalable AI system architectures supporting real-time and batch AI workloads
• Build and orchestrate multi-agent AI systems capable of autonomous reasoning and task execution
• Implement agent workflows using modern orchestration frameworks
• Design tool-enabled agents integrating with enterprise systems, APIs, and databases
• Develop Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge systems
• Implement vector search and semantic retrieval using modern vector databases
• Optimize document chunking, embedding strategies, and retrieval quality
• Build AI workflows using frameworks such as LangChain, LangGraph, LangSmith
• Implement advanced AI workflow orchestration and stateful agent pipelines
• Implement integrations using Model Context Protocol (MCP) to connect AI systems with enterprise tools and data sources
• Build AI-enabled automation workflows across internal platforms
• Deploy AI services in production environments with monitoring, scaling, and observability
• Implement CI/CD pipelines for AI applications
• Ensure model reliability, performance, and cost optimization
• Implement AI observability, evaluation, and monitoring frameworks
• Build automated pipelines for testing, validation, and continuous improvement of AI systems
• Lead and mentor AI engineers and developers
• Establish standard processes for AI system architecture and development
• Evaluate emerging AI tools, frameworks, and technologies

Requirements

• 7-12 years experience in AI system development
• Strong experience building LLM-powered applications
• Deep understanding of Agentic AI architectures, RAG, multi-agent systems, tool-using AI agents
• Experience with AI frameworks such as LangChain, LangGraph, LangSmith
• Hands-on experience with vector databases like Pinecone and Chroma
• Strong software engineering skills in Python
• Experience with containerization, microservices, cloud platforms (AWS, Azure)
• Experience in model deployment, inference optimization, AI service scaling and cost optimization
• Experience with embedding models and semantic search
• Knowledge graph or hybrid retrieval experience is a plus
• Experience in automotive marketing preferred
• Excellent analytical and problem-solving skills
• Ability to diagnose and troubleshoot problems quickly
• Motivated to learn new applications and domains
• Strong time management skills
• Ability to take full ownership of tasks and projects
• Experience with Agile/SCRUM process
• Excellent interpersonal, verbal and written communication skills
• Self-motivated and directed with a can-do attitude

Tech stack

Benefits