Senior AI Engineer

chargepoint

Remote 10 Years Exp Posted 39d ago

Architect and build LLM‑based applications such as copilots, chatbots, and AI agents
Design and optimize RAG and grounded AI systems using enterprise data
Lead development of agentic workflows with tool/function calling and multi‑step reasoning
Own backend services and APIs for AI inference and orchestration
Drive LLMOps / GenAIOps practices (evaluation, monitoring, CI/CD, versioning)
Optimize AI systems for quality, cost, latency, and reliability
Apply and advocate for Responsible AI and security‑by‑design
Mentor engineers and influence AI engineering best practices
Partner with product, platform, and security teams to shape AI strategy

Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
Strong foundation in distributed systems design, microservices architecture, and event-driven patterns
Ability to balance speed, quality, and risk in production AI deployments
Passion for building scalable, maintainable, and responsible AI platforms
Strong communication skills with engineers, product managers, and leadership

10+ years of professional software engineering experience
Strong development skills in Python; experience with Java, FastAPI, Django, and modern backend frameworks for AI service development
Extensive hands-on experience with LLMs and generative AI systems
Strong experience with RAG, embeddings, Elasticsearch including vector and hybrid search, and prompt engineering
Experience building Copilot-style, conversational, and agent-based AI systems
Strong understanding of distributed systems, APIs, microservices architecture, and event-driven patterns
Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
- Familiarity with LLMOps and MLOps practices