Description

We are looking for a Senior AI Platform Engineer to join our AI team building our AI-powered customer experience platform. This role is fully focused on building, shipping, and maintaining production AI systems including LLM integrations, RAG pipelines, AI agent workflows, and supporting infrastructure.

Responsibilities

The ideal candidate brings hands-on experience building AI-powered features in production, strong fundamentals in prompt engineering and LLM integration patterns, and the ability to work independently in a fast-moving environment. You will work closely with architects and cross-functional teams to turn AI capabilities into reliable, scalable platform Responsibilities :

Design, build, and maintain AI agent workflows and orchestration patterns using frameworks like LangGraph.
Build and optimize production-grade RAG systems chunking strategies, retrieval pipelines, embedding generation, and response quality.
Implement and manage LLM API integrations with proper retry logic, fallbacks, rate limiting, error handling, and cost optimization.
Develop prompt engineering solutions including system prompts, few-shot patterns, structured outputs (JSON mode), and prompt versioning.
Build input validation, output filtering, and content safety layers for production AI systems.
Implement AI observability and evaluation tracing, automated quality checks, regression testing for AI outputs.
Build data ingestion pipelines for AI systems (document processing, embedding generation, vector storage).
Collaborate with architects and product teams to translate AI capabilities into reliable platform features.
Write well-tested, production-ready code with unit tests, integration tests, and AI-specific tests.
Contribute to design docs, runbooks, and technical documentation for AI systems.

Requirements

Must Have :

5+ years of professional software development experience.
Hands-on experience building AI/ML features or LLM-powered systems in production.
Strong understanding of LLM fundamentals tokens, context windows, embeddings, temperature, and similarity search.
Experience with RAG systems indexing strategies, retrieval methods, chunking, and when RAG is the right approach.
Practical prompt engineering skills chain-of-thought, few-shot, structured outputs, and systematic iteration.
Experience with at least one AI orchestration framework (LangGraph, LangChain, or equivalent).
Working experience with at least one vector database (pgvector, Pinecone, Qdrant, Weaviate, or similar).
Proficiency in Python for AI development and prototyping.
Experience with LLM APIs (Claude SDK, OpenAI SDK, or similar) in production.
Understanding of AI safety basics prompt injection, jailbreaking, and practical mitigation approaches.
Working knowledge of cloud platforms (AWS preferred) and containerization (Docker, Kubernetes).
Strong problem-solving skills and ability to break down ambiguous AI problems into implementable tasks.

Nice To Have

Experience with AI observability tools (LangSmith, LangFuse) for tracing and debugging.
Experience with MCP (Model Context Protocol) or equivalent tool integration patterns.
Familiarity with fine-tuning concepts and when to consider fine-tuning vs. prompt-based solutions.
Programming experience in Java
Experience with event-driven architectures and message queues (Kafka, RabbitMQ).
Knowledge of the telecom domain (billing, CRM, customer lifecycle).
Experience shipping AI features in a customer-facing product.
Backend experience in Go, Node.js, or Java microservices.

(ref:hirist.tech)

Senior AI Platform Engineer - LLM/RAG