Senior AI Engineer
About the role
The Senior AI Engineer is responsible for designing, building, and operating production-grade AI agents, orchestration frameworks, and intelligent automation systems to support the organization's customer, operational, and enterprise functions. The role involves developing scalable conversational systems, integrating AI with backend systems, and ensuring solutions meet production standards for accuracy, reliability, and safety. The engineer will collaborate with cross-functional teams, mentor junior engineers, and contribute to the continuous improvement of AI engineering practices. Candidates should have strong experience in Python, AI/ML systems, and production deployment, as well as familiarity with multi-channel delivery and enterprise integration.
Must have
- Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
- Strong proficiency in Python for building production-grade AI/ML systems.
- Good understanding of agent workflows, tool usage, and execution patterns
- Familiarity with Model Context Protocol (MCP).
- Strong understanding of prompt engineering and structured prompting techniques.
- Ability to implement context persistence and memory strategies.
- Familiarity with multi-channel delivery (chat, WhatsApp, email, voice).
- Ability to integrate enterprise knowledge sources (documents, APIs, structured data).
- Familiarity with guardrails, fallback strategies, and failure handling.
- Awareness of AI safety practices (e.g., prompt injection, output validation, guardrails).
- Strong experience in building REST APIs and microservices.
- Understanding of asynchronous processing and event-driven architecture.
- Familiarity with CI/CD pipelines and cloud environments.
- Understanding of scalability, reliability, and cost optimization basics.
- Understanding of monitoring, logging, and pe.
- Understanding of evaluation approaches for AI systems (testing, benchmarking)
- Ability to optimize for latency, cost (token usage), and response quality.
- Fluent in English Language.
- With 2+ years of hands-on experience building production GenAI systems.
- Hands-on experience designing AI agents and multi-agent orchestration systems.
- Experience designing multi-turn conversational systems and dialogue flows.
- Experience with Human-in-the-Loop (HITL) workflows.
- Experience with vector databases and semantic search.
- Hands-on experience building RAG pipelines.
- Experience integrating AI with enterprise backend systems.
- Experience with LLM APIs, SLMs, and agent frameworks.
- Experience with Docker and Kubernetes.
- Experience working with production-grade AI systems.
Technologies
- Agentic AI
- CI/CD
- Docker
- Event-Driven Architecture
- Generative AI
- Kubernetes
- LLM
- Machine Learning
- MCP
- Microservices
- Prompt Engineering
- Python
- RAG
- REST
- Semantic Search
- Vector Databases
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