AI Engineer

As an AI Engineer at Anaira, you will work on building intelligent AI Agent systems for enterprise customers across multiple domains. You will collaborate closely with product, engineering, and business teams to architect scalable AI solutions using LLMs, Retrieval-Augmented Generation (RAG), orchestration frameworks, vector databases, and workflow automation tools.

You will play a key role in developing production-ready AI systems capable of handling enterprise-grade requirements such as security, scalability, reliability, observability, and integration with internal/external systems.

Responsibilities:

• Design, build, and deploy AI Agents for enterprise workflows and business automation.
• Develop multi-agent systems capable of task orchestration, reasoning, memory handling, and workflow execution.
• Build and optimise Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources.
• Integrate AI Agents with enterprise applications, CRMs, ERPs, APIs, databases, and communication platforms.
• Work with Large Language Models (LLMs), including OpenAI, Anthropic, Gemini, Llama, and open-source models.
• Build scalable backend services and APIs for AI applications.
• Fine-tune prompts, optimise inference performance, and improve AI response quality.
• Implement guardrails, monitoring, evaluation frameworks, and observability for AI systems.
• Collaborate with product and customer success teams to understand client requirements and translate them into AI-driven solutions.
• Ensure enterprise-grade security, compliance, and reliability standards.
• Stay updated with advancements in Generative AI, Agentic AI, LLMOps, and AI infrastructure.

Requirements:

• Strong experience in Python and backend development.
• Hands-on experience with Generative AI and LLM-based applications.
• Experience building AI Agents using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
• Experience with RAG architectures and vector databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS.
• Strong understanding of prompt engineering and LLM optimisation.
• Experience integrating APIs, third-party systems, and enterprise platforms.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of Docker, Kubernetes, CI/CD pipelines, and scalable deployments.
• Understanding of AI evaluation metrics, monitoring, and observability tools.
• Experience working with SQL/NoSQL databases.

Preferred Skills:

• Experience working on enterprise AI products or SaaS platforms.
• Knowledge of MLOps / LLMOps practices.
• Exposure to fine-tuning, embeddings, and model optimisation.
• Experience with workflow automation platforms and AI orchestration.
• Familiarity with enterprise security and compliance standards.
• Experience working in a startup or high-growth environment.

Good to Have:

• Strong problem-solving and analytical thinking.
• Ability to work in fast-paced startup environments.
• Ownership mindset with the ability to build from 01
• Strong communication and stakeholder management skills.
• Passion for AI innovation and enterprise transformation.

Educational Qualification:

• Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field.
• Equivalent practical experience in AI engineering and product development is also valued.

Good to Have Experience:

Candidates with experience in the following areas will have an added advantage:

• AI Copilots
• Enterprise Search
• Conversational AI
• Autonomous Workflow Automation
• AI-driven Knowledge Management
• Multi-Agent Systems
• Voice AI / Speech Models
• AI Security and Governance