Senior AI Engineer

chargepoint

Bengaluru, India 8 Years Exp Posted 34d ago

Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

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 (Kafka, RabbitMQ)
Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
Background in computer vision, image processing, or visual transformer architectures
Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
Experience working with massive datasets (50TB+) and building scalable data pipelines
Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
Familiarity with RLHF-style preference tuning and model alignment techniques
Experience with observability and monitoring stacks including metrics, logging, and tracing
- Certifications in Generative AI, Agentic AI, or related specialization.