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 capabilities. The role involves close collaboration with engineers and cross-functional teams to ensure AI solutions are accurate, reliable, and scalable, forming the foundation for enterprise-grade AI platforms. Key responsibilities include developing AI agents and conversational systems, delivering AI-powered automation across multiple channels, integrating AI with backend systems, and ensuring production quality and reliability. The position also involves mentoring junior engineers and promoting engineering excellence.
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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