Experience
3 - 7 yrs
Job Location
Central Remote, Remote
Vacancy
1
Designation
Senior Artificial Intelligence Engineer
Job Type
ONSITE
Job Description
We are looking for a Senior AI Platform Engineer to join our AI team and help build a next-
generation AI-powered customer experience platform. This role focuses on designing,
developing, and maintaining production-grade AI systems, including LLM integrations,
RAG pipelines, AI agent workflows, and supporting infrastructure.
You will work closely with architects and cross-functional teams to transform AI
capabilities into scalable, reliable platform features. This role requires strong hands-on
experience with production AI systems, prompt engineering, and LLM integration patterns
in a fast-paced environment.
Key Responsibilities
Design, build, and maintain AI agent workflows and orchestration patterns (e.g.,
LangGraph)
Develop and optimize production-grade RAG systems (chunking, retrieval pipelines,
embeddings, response quality)
Implement and manage LLM API integrations with retry logic, fallbacks, rate limiting,
and cost optimization
Build advanced prompt engineering solutions (system prompts, few-shot learning,
structured outputs, versioning)
Develop input validation, output filtering, and AI safety layers
Implement AI observability and evaluation frameworks (tracing, regression testing,
quality checks)
Build data ingestion pipelines for AI systems (document processing, embeddings,
vector storage)
Collaborate with product and architecture teams to deliver scalable AI solutions
Write clean, testable, and production-ready code (unit, integration, and AI-specific tests)
Contribute to technical documentation, design docs, and operational runbooks
Must-Have Skills Experience
All rights reserved
Hands-on experience building AI/ML or LLM-powered systems in production
Strong understanding of LLM fundamentals (tokens, embeddings, context windows,
temperature, similarity search)
Experience with RAG systems (indexing, chunking strategies, retrieval methods)
Strong prompt engineering expertise (few-shot, structured outputs, iterative
improvements)
Experience with AI orchestration frameworks (LangGraph, LangChain, or similar)
Hands-on experience with vector databases (pgvector, Pinecone, Qdrant, Weaviate, etc.)
Strong proficiency in Python
Experience working with LLM APIs (OpenAI, Claude, or similar)
Understanding of AI safety concepts (prompt injection, jailbreaking, mitigation
strategies)
Experience with cloud platforms (AWS preferred) and containerization (Docker,
Kubernetes)
Strong analytical and problem-solving skills
Good-to-Have Skills
Experience with AI observability tools (LangSmith, LangFuse)
Familiarity with Model Context Protocol (MCP) or similar integration patterns
Experience with AI observability tools (LangSmith, LangFuse)
Familiarity with Model Context Protocol (MCP) or similar integration patterns
Understanding of fine-tuning vs prompt-based approaches
Programming experience in Java
Experience with event-driven systems (Kafka, RabbitMQ)
Telecom domain knowledge (billing, CRM, lifecycle management)
Experience building customer-facing AI products
Backend development experience (Go, Node.js, Java microservices)